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Nexha A, Pilz LK, Oliveira MAB, Xavier NB, Borges RB, Frey BN, Hidalgo MPL. Greater within- and between-day instability is associated with worse anxiety and depression symptoms. J Affect Disord 2024; 356:215-223. [PMID: 38582128 DOI: 10.1016/j.jad.2024.04.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 03/07/2024] [Accepted: 04/03/2024] [Indexed: 04/08/2024]
Abstract
BACKGROUND Depression and anxiety affect hundreds of millions of people worldwide, and their prevalence increased during the COVID-19 pandemic as social schedules were disrupted. This study explores the associations between anxiety and depression and within- and between-day instability of affective, somatic, and cognitive symptoms during the early pandemic stages. METHODS Participants (n = 153, ages 18-77, 72 % female) reported daily levels of affective (anxiety/sadness), somatic (appetite/sleepiness), and cognitive (concentration/energy) symptoms for 14-44 days at five timepoints: 0, 3, 6, 9, and 12 h after awakening. At the end of the study, participants completed validated scales for anxiety (GAD-7) and depression (PHQ-9). Symptom instability was assessed using the Absolute Real Variability (ARV) index. Regression models examined within-day instability (WD-I) and between-day instability (BD-I) with GAD-7 and PHQ-9 scores as outcomes. RESULTS Greater instability (both WD-I and BD-I) of affective symptoms correlated with elevated GAD-7 and PHQ-9 scores. For somatic and cognitive symptoms, greater BD-I was associated with higher scores. LIMITATIONS The study used retrospective daily data, which could benefit from real-time assessments for improved accuracy. CONCLUSIONS This study provides empirical evidence of a connection between greater anxiety and depression severity and increased instability in daily mood and physiological symptoms. The findings underscore the importance of consistent symptom monitoring to understand overall mental health trajectories. Additionally, it highlights the role of daily routines in stabilizing the circadian system, potentially regulating physiological and psychological processes and reducing symptom instability.
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Affiliation(s)
- Adile Nexha
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Canada.
| | - Luísa K Pilz
- Graduate Program in Psychiatry and Behavioral Sciences, Faculty of Medicine, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Laboratório de Cronobiologia e Sono, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil; Department of Anesthesiology and Intensive Care Medicine CCM/CVK, Charité - Universitätsmedizin Berlin, Berlin, Germany; ECRC Experimental and Clinical Research Center, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Melissa A B Oliveira
- Graduate Program in Psychiatry and Behavioral Sciences, Faculty of Medicine, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Laboratório de Cronobiologia e Sono, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
| | - Nicoli B Xavier
- Graduate Program in Psychiatry and Behavioral Sciences, Faculty of Medicine, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Laboratório de Cronobiologia e Sono, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
| | - Rogério Boff Borges
- Biostatistics Unit - Research Board (DIPE), Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil; Department of Statistics, Institute of Mathematics and Statistics, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Benicio N Frey
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Canada; Mood Disorders Program, St. Joseph's Healthcare Hamilton, Hamilton, Canada; Women's Health Concerns Clinic, St. Joseph's Healthcare Hamilton, Hamilton, Canada
| | - Maria Paz L Hidalgo
- Graduate Program in Psychiatry and Behavioral Sciences, Faculty of Medicine, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Laboratório de Cronobiologia e Sono, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
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Varidel M, Hickie IB, Prodan A, Skinner A, Marchant R, Cripps S, Oliveria R, Chong MK, Scott E, Scott J, Iorfino F. Dynamic learning of individual-level suicidal ideation trajectories to enhance mental health care. NPJ MENTAL HEALTH RESEARCH 2024; 3:26. [PMID: 38849429 PMCID: PMC11161660 DOI: 10.1038/s44184-024-00071-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 04/25/2024] [Indexed: 06/09/2024]
Abstract
There has recently been an increase in ongoing patient-report routine outcome monitoring for individuals within clinical care, which has corresponded to increased longitudinal information about an individual. However, many models that are aimed at clinical practice have difficulty fully incorporating this information. This is in part due to the difficulty in dealing with the irregularly time-spaced observations that are common in clinical data. Consequently, we built individual-level continuous-time trajectory models of suicidal ideation for a clinical population (N = 585) with data collected via a digital platform. We demonstrate how such models predict an individual's level and variability of future suicide ideation, with implications for the frequency that individuals may need to be observed. These individual-level predictions provide a more personalised understanding than other predictive methods and have implications for enhanced measurement-based care.
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Affiliation(s)
- Mathew Varidel
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia.
| | - Ian B Hickie
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia
| | - Ante Prodan
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia
- Translational Health Research Institute, Western Sydney University, Sydney, NSW, Australia
- School of Computer, Data and Mathematical Sciences, Western Sydney University, Sydney, NSW, Australia
| | - Adam Skinner
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia
| | - Roman Marchant
- Human Technology Institute, University of Technology, Sydney, NSW, Australia
- School of Mathematical and Physical Sciences, University of Technology Sydney, Sydney, NSW, Australia
| | - Sally Cripps
- Human Technology Institute, University of Technology, Sydney, NSW, Australia
- School of Mathematical and Physical Sciences, University of Technology Sydney, Sydney, NSW, Australia
| | | | - Min K Chong
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia
| | - Elizabeth Scott
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia
| | - Jan Scott
- Academic Psychiatry, Institute of Neuroscience, Newcastle University, Newcastle, UK
| | - Frank Iorfino
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia
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Ho FYY, Poon CY, Wong VWH, Chan KW, Law KW, Yeung WF, Chung KF. Actigraphic monitoring of sleep and circadian rest-activity rhythm in individuals with major depressive disorder or depressive symptoms: A meta-analysis. J Affect Disord 2024; 361:224-244. [PMID: 38851435 DOI: 10.1016/j.jad.2024.05.155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 05/10/2024] [Accepted: 05/28/2024] [Indexed: 06/10/2024]
Abstract
BACKGROUND Disrupted sleep and rest-activity pattern are common clinical features in depressed individuals. This meta-analysis compared sleep and circadian rest-activity rhythms in people with major depressive disorder (MDD) or depressive symptoms and healthy controls. METHODS Eligible studies were identified in five databases up to December 2023. The search yielded 53 studies with a total of 11,115 participants, including 4000 depressed participants and 7115 healthy controls. RESULTS Pooled meta-analyses demonstrated that depressed individuals have significantly longer sleep latency (SMD = 0.23, 95 % CI: 0.12 to 0.33) and wake time after sleep onset (SMD = 0.37, 95 % CI: 0.22 to 0.52), lower sleep efficiency (SMD = -0.41, 95 % CI: -0.56 to -0.25), more nocturnal awakenings (SMD = 0.58, 95 % CI: 0.29 to 0.88), lower MESOR (SMD = -0.54, 95 % CI: -0.81 to -0.28), amplitude (SMD = -0.33, 95 % CI: -0.57 to -0.09), and interdaily stability (SMD = -0.17, 95 % CI: -0.28 to -0.05), less daytime (SMD = -0.79, 95 % CI: -1.08 to -0.49) and total activities (SMD = -0.89, 95 % CI: -1.28 to -0.50) when compared with healthy controls. LIMITATIONS Most of the included studies reported separate sleep and activity parameters instead of 24-hour rest-activity rhythms. The variabilities among actigraphy devices and the types of participants recruited also impede precise comparisons. CONCLUSIONS The findings emerging from this study offered a better understanding of sleep and rest-activity rhythm in individuals with MDD or depressive symptoms. Future studies could advocate for deriving objective, distinctive 24-hour rest-activity profiles contributing to the risk of depression. PROSPERO REGISTRATION NUMBER CRD42021259780.
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Affiliation(s)
- Fiona Yan-Yee Ho
- Department of Psychology, The Chinese University of Hong Kong, Hong Kong.
| | - Chun-Yin Poon
- Department of Psychology, The Chinese University of Hong Kong, Hong Kong
| | | | - Ka-Wai Chan
- Department of Psychology, The Chinese University of Hong Kong, Hong Kong
| | - Ka-Wai Law
- Department of Psychology, The Chinese University of Hong Kong, Hong Kong
| | - Wing-Fai Yeung
- School of Nursing, The Hong Kong Polytechnic University, Hong Kong
| | - Ka-Fai Chung
- Department of Psychiatry, The University of Hong Kong, Hong Kong
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Timm I, Giurgiu M, Ebner-Priemer U, Reichert M. The Within-Subject Association of Physical Behavior and Affective Well-Being in Everyday Life: A Systematic Literature Review. Sports Med 2024:10.1007/s40279-024-02016-1. [PMID: 38705972 DOI: 10.1007/s40279-024-02016-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/01/2024] [Indexed: 05/07/2024]
Abstract
BACKGROUND The interplay of physical activity (PA) with affective well-being (AWB) is highly critical to both health behaviors and health outcomes. Current prominent theories presume AWB to be crucial for PA maintenance, and PA is evidenced to foster mental health. However, thus far, PA-AWB associations have mainly been researched in laboratory settings and with interventional designs, but the everyday life perspective had not been focused on, mostly due to technological limitations. In the course of digitization, the number of studies using device-based methods to research the within-subject association of physical activity and affective well-being (PA-AWB) under ecological valid conditions increased rapidly, but a recent comprehensive systematic review of evidence across populations, age groups, and distinct AWB components remained inconclusive. OBJECTIVES Therefore, we aimed to firstly review daily-life studies that assessed intensive longitudinal device-based (e.g., electronic smartphone diaries and accelerometry) and real-time PA-AWB data, secondly to develop and apply a quality assessment tool applicable to those studies, and thirdly to discuss findings and draw implications for research and practice. METHODS To this end, the literature was searched in three databases (Web of Science, PubMed, Scopus) up to November 2022. The systematic review followed the PRISMA guidelines and had been pre-registered (PROSPERO id: CRD42021277327). A modified quality assessment tool was developed to illustrate the risk of bias of included studies. RESULTS The review of findings showed that, in general, already short PA bouts in everyday life, which clearly differ from structured exercise sessions, are positively associated with AWB. In particular, feelings of energy relate to incidental (non-exercise and unstructured) activity, and PA-AWB associations depend on population characteristics. The quality assessment revealed overall moderate study quality; however, the methods applied were largely heterogeneous between investigations. Overall, the reviewed evidence on PA-AWB associations in everyday life is ambiguous; for example, no clear patterns of directions and strengths of PA-AWB relationships depending on PA and AWB components (such as intensity, emotions, affect, mood) emerged. CONCLUSIONS The reviewed evidence can fuel discussions on whether the World Health Organization's notion "every move counts" may be extended to everyday life AWB. Concurrently, the PA-AWB relationship findings endorse prominent theories highlighting the critical role of AWB in everyday PA engagement and maintenance. However, the review also clearly highlights the need to advance and harmonize methodological approaches for more fine-grained investigations on which specific PA/AWB characteristics, contextual factors, and biological determinants underly PA-AWB associations in everyday life. This will enable the field to tackle pressing challenges such as the issue of causality of PA-AWB associations, which will help to shape and refine existing theories to ultimately predict and improve health behavior, thereby feeding into precision medicine approaches.
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Affiliation(s)
- Irina Timm
- Mental mHealth Lab, Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Hertzstr. 16, 76187, Karlsruhe, Germany.
| | - Marco Giurgiu
- Mental mHealth Lab, Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Hertzstr. 16, 76187, Karlsruhe, Germany
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany
| | - Ulrich Ebner-Priemer
- Mental mHealth Lab, Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Hertzstr. 16, 76187, Karlsruhe, Germany
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany
- German Center for Mental Health (DZPG), partner site Mannheim, Mannheim, Germany
| | - Markus Reichert
- Mental mHealth Lab, Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Hertzstr. 16, 76187, Karlsruhe, Germany.
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany.
- Department of eHealth and Sports Analytics, Faculty of Sport Science, Ruhr University Bochum, Gesundheitscampus-Nord 10, 44801, Bochum, Germany.
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Beaglehole B, Porter R, Douglas K, Lacey CJ, de Bie A, Jordan J, Mentzel C, Thwaites B, Manuel J, Murray G, Frampton C, Glue P. Protocol for a randomised controlled trial of ketamine versus ketamine and behavioural activation therapy for adults with treatment-resistant depression in the community. BMJ Open 2024; 14:e084844. [PMID: 38692731 PMCID: PMC11086269 DOI: 10.1136/bmjopen-2024-084844] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Accepted: 04/03/2024] [Indexed: 05/03/2024] Open
Abstract
INTRODUCTION Although short-term benefits follow parenteral ketamine for treatment-resistant major depressive disorder (TR-MDD), there are challenges that prevent routine use of ketamine by clinicians. These include acute dissociative effects of parenteral ketamine, high relapse rates following ketamine dosing and the uncertain role of psychotherapy. This randomised controlled trial (RCT) seeks to establish the feasibility of evaluating repeated oral doses of ketamine and behavioural activation therapy (BAT), compared with ketamine treatment alone, for TR-MDD. We also aim to compare relapse rates between treatment arms to determine the effect size of adding BAT to oral ketamine. METHODS AND ANALYSIS This is a prospectively registered, two-centre, single-blind RCT. We aim to recruit 60 participants with TR-MDD aged between 18 and 65 years. Participants will be randomised to 8 weeks of oral ketamine and BAT, or 8 weeks of oral ketamine alone. Feasibility will be assessed by tracking attendance for ketamine and BAT, acceptability of treatment measures and retention to the study follow-up protocol. The primary efficacy outcome measure is the Montgomery-Asberg Depression Rating Scale (MADRS) measured weekly during treatment and fortnightly during 12 weeks of follow-up. Other outcome measures will assess the tolerability of ketamine and BAT, cognition and activity (using actigraphy). Participants will be categorised as non-responders, responders, remitters and relapsed during follow-up. MADRS scores will be analysed using a linear mixed model. For a definitive follow-up RCT study to be recommended, the recruitment expectations will be met and efficacy outcomes consistent with a >20% reduction in relapse rates favouring the BAT and ketamine arm will be achieved. ETHICS AND DISSEMINATION Ethics approval was granted by the New Zealand Central Health and Disability Ethics Committee (reference: 2023 FULL18176). Study findings will be reported to participants, stakeholder groups, conferences and peer-reviewed publications. TRIAL REGISTRATION NUMBER UTN: U1111-1294-9310, ACTRN12623000817640p.
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Affiliation(s)
- Ben Beaglehole
- Psychological Medicine, University of Otago, Christchurch, New Zealand
| | - Richard Porter
- Psychological Medicine, University of Otago, Christchurch, New Zealand
| | - Katie Douglas
- Psychological Medicine, University of Otago, Christchurch, New Zealand
| | | | - Aroha de Bie
- Te Whatu Ora-Health New Zealand Waitaha Canterbury, Christchurch, Canterbury, New Zealand
| | - Jennifer Jordan
- Psychological Medicine, University of Otago, Christchurch, New Zealand
| | - Charlie Mentzel
- Department of Psychological Medicine, University of Otago, Dunedin, New Zealand
| | | | - Jenni Manuel
- Psychological Medicine, University of Otago, Christchurch, New Zealand
| | - Greg Murray
- Centre for Mental Health, Swinburne University of Technology, Hawthorn, Victoria, Australia
| | | | - Paul Glue
- Psychological Medicine, University of Otago, Dunedin School of Medicine, Dunedin, New Zealand
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Nan J, Herbert MS, Purpura S, Henneken AN, Ramanathan D, Mishra J. Personalized Machine Learning-Based Prediction of Wellbeing and Empathy in Healthcare Professionals. SENSORS (BASEL, SWITZERLAND) 2024; 24:2640. [PMID: 38676258 PMCID: PMC11053570 DOI: 10.3390/s24082640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Revised: 04/09/2024] [Accepted: 04/19/2024] [Indexed: 04/28/2024]
Abstract
Healthcare professionals are known to suffer from workplace stress and burnout, which can negatively affect their empathy for patients and quality of care. While existing research has identified factors associated with wellbeing and empathy in healthcare professionals, these efforts are typically focused on the group level, ignoring potentially important individual differences and implications for individualized intervention approaches. In the current study, we implemented N-of-1 personalized machine learning (PML) to predict wellbeing and empathy in healthcare professionals at the individual level, leveraging ecological momentary assessments (EMAs) and smartwatch wearable data. A total of 47 mood and lifestyle feature variables (relating to sleep, diet, exercise, and social connections) were collected daily for up to three months followed by applying eight supervised machine learning (ML) models in a PML pipeline to predict wellbeing and empathy separately. Predictive insight into the model architecture was obtained using Shapley statistics for each of the best-fit personalized models, ranking the importance of each feature for each participant. The best-fit model and top features varied across participants, with anxious mood (13/19) and depressed mood (10/19) being the top predictors in most models. Social connection was a top predictor for wellbeing in 9/12 participants but not for empathy models (1/7). Additionally, empathy and wellbeing were the top predictors of each other in 64% of cases. These findings highlight shared and individual features of wellbeing and empathy in healthcare professionals and suggest that a one-size-fits-all approach to addressing modifiable factors to improve wellbeing and empathy will likely be suboptimal. In the future, such personalized models may serve as actionable insights for healthcare professionals that lead to increased wellness and quality of patient care.
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Affiliation(s)
- Jason Nan
- Neural Engineering and Translation Labs, University of California San Diego, La Jolla, CA 92093, USA; (S.P.); (D.R.); (J.M.)
- Department of Bioengineering, University of California San Diego, La Jolla, CA 92093, USA
| | - Matthew S. Herbert
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA;
- Department of Mental Health, VA San Diego Medical Center, San Diego, CA 92161, USA;
- Center of Excellence for Stress and Mental Health, VA San Diego Medical Center, San Diego, CA 92161, USA
| | - Suzanna Purpura
- Neural Engineering and Translation Labs, University of California San Diego, La Jolla, CA 92093, USA; (S.P.); (D.R.); (J.M.)
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA;
| | - Andrea N. Henneken
- Department of Mental Health, VA San Diego Medical Center, San Diego, CA 92161, USA;
- Center of Excellence for Stress and Mental Health, VA San Diego Medical Center, San Diego, CA 92161, USA
| | - Dhakshin Ramanathan
- Neural Engineering and Translation Labs, University of California San Diego, La Jolla, CA 92093, USA; (S.P.); (D.R.); (J.M.)
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA;
- Department of Mental Health, VA San Diego Medical Center, San Diego, CA 92161, USA;
- Center of Excellence for Stress and Mental Health, VA San Diego Medical Center, San Diego, CA 92161, USA
| | - Jyoti Mishra
- Neural Engineering and Translation Labs, University of California San Diego, La Jolla, CA 92093, USA; (S.P.); (D.R.); (J.M.)
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA;
- Center of Excellence for Stress and Mental Health, VA San Diego Medical Center, San Diego, CA 92161, USA
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Strejilevich S, Samamé C, Marengo E, Godoy A, Smith J, Camino S, Oppel M, Sobrero M, López Escalona L. Can we predict a "tsunami"? Symptomatic and syndromal density, mood instability and treatment intensity in people with bipolar disorders under a strict and long lockdown. J Affect Disord 2024; 351:827-832. [PMID: 38341152 DOI: 10.1016/j.jad.2024.02.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 07/18/2023] [Accepted: 02/06/2024] [Indexed: 02/12/2024]
Abstract
BACKGROUND Converging evidence supports the involvement of circadian rhythm disturbances in the course and morbidity of bipolar disorders (BD). During 2020, lockdown measures were introduced worldwide to contain the health crisis caused by the COVID-19 pandemic. As a result, chronobiological rhythms were critically disrupted and illness outcomes were expected to worsen. The current study aimed to explore changes in morbidity among BD patients living under lockdown. METHODS Ninety BD outpatients under naturalistic treatment conditions were followed from March to September 2020 using a mood chart technique. Different treatment and illness variables, including mood instability, were assessed and compared with the outcomes obtained during the same 28-week period in 2019. RESULTS For most clinical variables, no significant differences were observed between time periods. A slight decrease was found in symptom intensity (from 15.19 ± 20.62 to 10.34 ± 15.79, FDR-adjusted p = 0.04) and in the number of depressive episodes (from 0.39 ± 0.74 to 0.22 ± 0.63, FDR-adjusted p = 0.03), whereas the intensity of pharmacological treatment remained unchanged. Previous illness course predicted mood outcomes during the confinement. LIMITATIONS Follow-up periods were relatively short. Further, actigraphy or other methods capable of ensuring significant changes in physical activity were not used. CONCLUSIONS In line with other studies, our findings show no worsening in the clinical morbidity of BD patients during lockdown. This conspicuous contrast between our initial predictions and the observed findings highlights the fact that we are still far from being able to provide accurate predictive models for BD.
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Affiliation(s)
- Sergio Strejilevich
- ÁREA, Asistencia e Investigación en Trastornos del Ánimo, Buenos Aires, Argentina.
| | - Cecilia Samamé
- Departamento de Psicología, Universidad Católica del Uruguay, Montevideo, Uruguay
| | - Eliana Marengo
- ÁREA, Asistencia e Investigación en Trastornos del Ánimo, Buenos Aires, Argentina
| | - Antonella Godoy
- ÁREA, Asistencia e Investigación en Trastornos del Ánimo, Buenos Aires, Argentina
| | - José Smith
- ÁREA, Asistencia e Investigación en Trastornos del Ánimo, Buenos Aires, Argentina
| | - Sebastián Camino
- ÁREA, Asistencia e Investigación en Trastornos del Ánimo, Buenos Aires, Argentina
| | - Melany Oppel
- ÁREA, Asistencia e Investigación en Trastornos del Ánimo, Buenos Aires, Argentina
| | - Martina Sobrero
- ÁREA, Asistencia e Investigación en Trastornos del Ánimo, Buenos Aires, Argentina
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Song YM, Jeong J, de Los Reyes AA, Lim D, Cho CH, Yeom JW, Lee T, Lee JB, Lee HJ, Kim JK. Causal dynamics of sleep, circadian rhythm, and mood symptoms in patients with major depression and bipolar disorder: insights from longitudinal wearable device data. EBioMedicine 2024; 103:105094. [PMID: 38579366 PMCID: PMC11002811 DOI: 10.1016/j.ebiom.2024.105094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Revised: 03/14/2024] [Accepted: 03/17/2024] [Indexed: 04/07/2024] Open
Abstract
BACKGROUND Sleep and circadian rhythm disruptions are common in patients with mood disorders. The intricate relationship between these disruptions and mood has been investigated, but their causal dynamics remain unknown. METHODS We analysed data from 139 patients (76 female, mean age = 23.5 ± 3.64 years) with mood disorders who participated in a prospective observational study in South Korea. The patients wore wearable devices to monitor sleep and engaged in smartphone-delivered ecological momentary assessment of mood symptoms. Using a mathematical model, we estimated their daily circadian phase based on sleep data. Subsequently, we obtained daily time series for sleep/circadian phase estimates and mood symptoms spanning >40,000 days. We analysed the causal relationship between the time series using transfer entropy, a non-linear causal inference method. FINDINGS The transfer entropy analysis suggested causality from circadian phase disturbance to mood symptoms in both patients with MDD (n = 45) and BD type I (n = 35), as 66.7% and 85.7% of the patients with a large dataset (>600 days) showed causality, but not in patients with BD type II (n = 59). Surprisingly, no causal relationship was suggested between sleep phase disturbances and mood symptoms. INTERPRETATION Our findings suggest that in patients with mood disorders, circadian phase disturbances directly precede mood symptoms. This underscores the potential of targeting circadian rhythms in digital medicine, such as sleep or light exposure interventions, to restore circadian phase and thereby manage mood disorders effectively. FUNDING Institute for Basic Science, the Human Frontiers Science Program Organization, the National Research Foundation of Korea, and the Ministry of Health & Welfare of South Korea.
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Affiliation(s)
- Yun Min Song
- Department of Mathematical Sciences, KAIST, Daejeon, 34141, Republic of Korea; Biomedical Mathematics Group, Pioneer Research Center for Mathematical and Computational Sciences, Institute for Basic Science, Daejeon, 34126, Republic of Korea
| | - Jaegwon Jeong
- Department of Psychiatry, Korea University College of Medicine, Seoul, 02841, Republic of Korea; Chronobiology Institute, Korea University, Seoul, 02841, Republic of Korea
| | - Aurelio A de Los Reyes
- Biomedical Mathematics Group, Pioneer Research Center for Mathematical and Computational Sciences, Institute for Basic Science, Daejeon, 34126, Republic of Korea; Institute of Mathematics, University of the Philippines Diliman, Quezon City, 1101, Philippines
| | - Dongju Lim
- Department of Mathematical Sciences, KAIST, Daejeon, 34141, Republic of Korea; Biomedical Mathematics Group, Pioneer Research Center for Mathematical and Computational Sciences, Institute for Basic Science, Daejeon, 34126, Republic of Korea
| | - Chul-Hyun Cho
- Department of Psychiatry, Korea University College of Medicine, Seoul, 02841, Republic of Korea; Chronobiology Institute, Korea University, Seoul, 02841, Republic of Korea
| | - Ji Won Yeom
- Department of Psychiatry, Korea University College of Medicine, Seoul, 02841, Republic of Korea; Chronobiology Institute, Korea University, Seoul, 02841, Republic of Korea
| | - Taek Lee
- Division of Computer Science and Engineering, Sun Moon University, Asan, 31460, Republic of Korea
| | - Jung-Been Lee
- Division of Computer Science and Engineering, Sun Moon University, Asan, 31460, Republic of Korea
| | - Heon-Jeong Lee
- Department of Psychiatry, Korea University College of Medicine, Seoul, 02841, Republic of Korea; Chronobiology Institute, Korea University, Seoul, 02841, Republic of Korea.
| | - Jae Kyoung Kim
- Department of Mathematical Sciences, KAIST, Daejeon, 34141, Republic of Korea; Biomedical Mathematics Group, Pioneer Research Center for Mathematical and Computational Sciences, Institute for Basic Science, Daejeon, 34126, Republic of Korea.
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Lateef TM, Dey D, Leroux A, Cui L, Xiao M, Zipunnikov V, Merikangas KR. Association Between Electronic Diary-Rated Sleep, Mood, Energy, and Stress With Incident Headache in a Community-Based Sample. Neurology 2024; 102:e208102. [PMID: 38266217 DOI: 10.1212/wnl.0000000000208102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 11/07/2023] [Indexed: 01/26/2024] Open
Abstract
BACKGROUND AND OBJECTIVES The aim of this study was to examine the diurnal links between average and changes in average levels of prospectively rated mood, sleep, energy, and stress as predictors of incident headache in a community-based sample. METHODS This observational study included structured clinical diagnostic assessment of both headache syndromes and mental disorders and electronic diaries that were administered 4 times per day for 2 weeks yielding a total of 4,974 assessments. The chief outcomes were incident morning (am) and later-day (pm) headaches. Generalized linear mixed-effects models were used to evaluate the average and lagged values of predictors including subjectively rated mood, anxiety, energy, stress, and sleep quality and objectively measured sleep duration and efficiency on incident am and pm headaches. RESULTS The sample included 477 participants (61% female), aged 7 through 84 years. After adjusting for demographic and clinical covariates and emotional states, incident am headache was associated with lower average (ß = -0.206*; confidence intervals: -0.397 to -0.017) and a decrease in average sleep quality on the prior day (ß = -0.172*; confidence interval: -0.305, -0.039). Average stress and changes in subjective energy levels on the prior day were associated with incident headaches but with different valence for am (decrease) (ß = -0.145* confidence interval: -0.286, -0.005) and pm (increase) (ß = 0.157*; confidence interval: 0.032, 0.281) headache. Mood and anxiety disorders were not significantly associated with incident headache after controlling for history of a diagnosis of migraine. DISCUSSION Both persistent and acute changes in arousal states manifest by subjective sleep quality and energy are salient precursors of incident headaches. Whereas poorer sleep quality and decreased energy on the prior day were associated with incident morning headache, an increase in energy and greater average stress were associated with headache onsets later in the day. Different patterns of predictors of morning and later-day incident headache highlight the role of circadian rhythms in the manifestations of headache. These findings may provide insight into the pathophysiologic processes underlying migraine and inform clinical intervention and prevention. Tracking these systems in real time with mobile technology provides a valuable ancillary tool to traditional clinical assessments.
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Affiliation(s)
- Tarannum M Lateef
- From the Children's National Health System (T.M.L.), Pediatric Specialists of Virginia, and George Washington University of Medicine; Intramural Research Program (T.M.L., D.D., L.C., K.R.M.), Section on Developmental Genetic Epidemiology, National Institute of Mental Health, Bethesda, MD; Department of Biostatistics and Informatics (A.L.), University of Colorado School of Public Health, Denver; Child Mind Institute (M.X.), New York; Department of Biostatistics (V.Z.); and Department of Epidemiology (K.R.M.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Debangan Dey
- From the Children's National Health System (T.M.L.), Pediatric Specialists of Virginia, and George Washington University of Medicine; Intramural Research Program (T.M.L., D.D., L.C., K.R.M.), Section on Developmental Genetic Epidemiology, National Institute of Mental Health, Bethesda, MD; Department of Biostatistics and Informatics (A.L.), University of Colorado School of Public Health, Denver; Child Mind Institute (M.X.), New York; Department of Biostatistics (V.Z.); and Department of Epidemiology (K.R.M.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Andrew Leroux
- From the Children's National Health System (T.M.L.), Pediatric Specialists of Virginia, and George Washington University of Medicine; Intramural Research Program (T.M.L., D.D., L.C., K.R.M.), Section on Developmental Genetic Epidemiology, National Institute of Mental Health, Bethesda, MD; Department of Biostatistics and Informatics (A.L.), University of Colorado School of Public Health, Denver; Child Mind Institute (M.X.), New York; Department of Biostatistics (V.Z.); and Department of Epidemiology (K.R.M.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Lihong Cui
- From the Children's National Health System (T.M.L.), Pediatric Specialists of Virginia, and George Washington University of Medicine; Intramural Research Program (T.M.L., D.D., L.C., K.R.M.), Section on Developmental Genetic Epidemiology, National Institute of Mental Health, Bethesda, MD; Department of Biostatistics and Informatics (A.L.), University of Colorado School of Public Health, Denver; Child Mind Institute (M.X.), New York; Department of Biostatistics (V.Z.); and Department of Epidemiology (K.R.M.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Mike Xiao
- From the Children's National Health System (T.M.L.), Pediatric Specialists of Virginia, and George Washington University of Medicine; Intramural Research Program (T.M.L., D.D., L.C., K.R.M.), Section on Developmental Genetic Epidemiology, National Institute of Mental Health, Bethesda, MD; Department of Biostatistics and Informatics (A.L.), University of Colorado School of Public Health, Denver; Child Mind Institute (M.X.), New York; Department of Biostatistics (V.Z.); and Department of Epidemiology (K.R.M.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Vadim Zipunnikov
- From the Children's National Health System (T.M.L.), Pediatric Specialists of Virginia, and George Washington University of Medicine; Intramural Research Program (T.M.L., D.D., L.C., K.R.M.), Section on Developmental Genetic Epidemiology, National Institute of Mental Health, Bethesda, MD; Department of Biostatistics and Informatics (A.L.), University of Colorado School of Public Health, Denver; Child Mind Institute (M.X.), New York; Department of Biostatistics (V.Z.); and Department of Epidemiology (K.R.M.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Kathleen R Merikangas
- From the Children's National Health System (T.M.L.), Pediatric Specialists of Virginia, and George Washington University of Medicine; Intramural Research Program (T.M.L., D.D., L.C., K.R.M.), Section on Developmental Genetic Epidemiology, National Institute of Mental Health, Bethesda, MD; Department of Biostatistics and Informatics (A.L.), University of Colorado School of Public Health, Denver; Child Mind Institute (M.X.), New York; Department of Biostatistics (V.Z.); and Department of Epidemiology (K.R.M.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
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10
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Meyer N, Lok R, Schmidt C, Kyle SD, McClung CA, Cajochen C, Scheer FAJL, Jones MW, Chellappa SL. The sleep-circadian interface: A window into mental disorders. Proc Natl Acad Sci U S A 2024; 121:e2214756121. [PMID: 38394243 PMCID: PMC10907245 DOI: 10.1073/pnas.2214756121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/25/2024] Open
Abstract
Sleep, circadian rhythms, and mental health are reciprocally interlinked. Disruption to the quality, continuity, and timing of sleep can precipitate or exacerbate psychiatric symptoms in susceptible individuals, while treatments that target sleep-circadian disturbances can alleviate psychopathology. Conversely, psychiatric symptoms can reciprocally exacerbate poor sleep and disrupt clock-controlled processes. Despite progress in elucidating underlying mechanisms, a cohesive approach that integrates the dynamic interactions between psychiatric disorder with both sleep and circadian processes is lacking. This review synthesizes recent evidence for sleep-circadian dysfunction as a transdiagnostic contributor to a range of psychiatric disorders, with an emphasis on biological mechanisms. We highlight observations from adolescent and young adults, who are at greatest risk of developing mental disorders, and for whom early detection and intervention promise the greatest benefit. In particular, we aim to a) integrate sleep and circadian factors implicated in the pathophysiology and treatment of mood, anxiety, and psychosis spectrum disorders, with a transdiagnostic perspective; b) highlight the need to reframe existing knowledge and adopt an integrated approach which recognizes the interaction between sleep and circadian factors; and c) identify important gaps and opportunities for further research.
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Affiliation(s)
- Nicholas Meyer
- Insomnia and Behavioural Sleep Medicine Clinic, University College London Hospitals NHS Foundation Trust, LondonWC1N 3HR, United Kingdom
- Department of Psychosis Studies, Institute of Psychology, Psychiatry, and Neuroscience, King’s College London, LondonSE5 8AF, United Kingdom
| | - Renske Lok
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA94305
| | - Christina Schmidt
- Sleep & Chronobiology Group, GIGA-Institute, CRC-In Vivo Imaging Unit, University of Liège, Liège, Belgium
- Psychology and Neuroscience of Cognition Research Unit, Faculty of Psychology, Speech and Language, University of Liège, Liège4000, Belgium
| | - Simon D. Kyle
- Sir Jules Thorn Sleep and Circadian Neuroscience Institute, Nuffield Department of Clinical Neurosciences, University of Oxford, OxfordOX1 3QU, United Kingdom
| | - Colleen A. McClung
- Translational Neuroscience Program, Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA15219
| | - Christian Cajochen
- Centre for Chronobiology, Department for Adult Psychiatry, Psychiatric Hospital of the University of Basel, BaselCH-4002, Switzerland
- Research Cluster Molecular and Cognitive Neurosciences, Department of Biomedicine, University of Basel, BaselCH-4055, Switzerland
| | - Frank A. J. L. Scheer
- Medical Chronobiology Program, Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women’s Hospital, Boston, MA02115
- Medical Chronobiology Program, Division of Sleep and Circadian Disorders, Department of Neurology, Brigham and Women’s Hospital, Boston, MA02115
- Division of Sleep Medicine, Harvard Medical School, Boston, MA02115
| | - Matthew W. Jones
- School of Physiology, Pharmacology and Neuroscience, Faculty of Health and Life Sciences, University of Bristol, BristolBS8 1TD, United Kingdom
| | - Sarah L. Chellappa
- School of Psychology, Faculty of Environmental and Life Sciences, University of Southampton, SouthamptonSO17 1BJ, United Kingdom
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11
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Hickie IB, Crouse JJ. Sleep and circadian rhythm disturbances: plausible pathways to major mental disorders? World Psychiatry 2024; 23:150-151. [PMID: 38214638 PMCID: PMC10786001 DOI: 10.1002/wps.21154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/13/2024] Open
Affiliation(s)
- Ian B Hickie
- Youth Mental Health and Technology Team, Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia
| | - Jacob J Crouse
- Youth Mental Health and Technology Team, Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia
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12
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Poon CY, Cheng YC, Wong VWH, Tam HK, Chung KF, Yeung WF, Ho FYY. Directional associations among real-time activity, sleep, mood, and daytime symptoms in major depressive disorder using actigraphy and ecological momentary assessment. Behav Res Ther 2024; 173:104464. [PMID: 38159415 DOI: 10.1016/j.brat.2023.104464] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 12/07/2023] [Accepted: 12/11/2023] [Indexed: 01/03/2024]
Abstract
Previous research has suggested that individuals with major depressive disorder (MDD) experienced alterations in sleep and activity levels. However, the temporal associations among sleep, activity levels, mood, and daytime symptoms in MDD have not been fully investigated. The present study aimed to fill this gap by utilizing real-time data collected across time points and days. 75 individuals with MDD and 75 age- and gender-matched healthy controls were recruited. Ecological momentary assessments (EMA) were adopted to assess real-time mood status for 7 days, and actigraphy was employed to measure day-to-day sleep-activity patterns. Multilevel modeling analyses were performed. Results revealed a bidirectional association between mood/daytime symptoms and activity levels across EMA intervals. Increased activity levels were predictive of higher alert cognition and positive mood, while an increase in positive mood also predicted more increase in activity levels in depressed individuals. A bidirectional association between sleep and daytime symptoms was also found. Alert cognition was found to be predictive of better sleep in the subsequent night. Contrariwise, higher sleep efficiency predicted improved alert cognition and sleepiness/fatigue the next day. A unidirectional association between sleep and activity levels suggested that higher daytime activity levels predicted a larger increase in sleep efficiency among depressed individuals. This study indicated how mood, activity levels, and sleep were temporally and intricately linked to each other in depressed individuals using actigraphy and EMA. It could pave the way for novel and efficacious treatments for depression that target not just mood but sleep and activity levels.
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Affiliation(s)
- Chun-Yin Poon
- Department of Psychology, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Yui-Ching Cheng
- Alice Ho Miu Ling Nethersole Hospital, Hospital Authority, Tai Po, Hong Kong
| | | | - Hon-Kwong Tam
- Pamela Youde Nethersole Eastern Hospital, Hospital Authority, Chai Wan, Hong Kong
| | - Ka-Fai Chung
- Department of Psychiatry, The University of Hong Kong, Pokfulam, Hong Kong
| | - Wing-Fai Yeung
- School of Nursing, The Hong Kong Polytechnic University, Hunghom, Hong Kong
| | - Fiona Yan-Yee Ho
- Department of Psychology, The Chinese University of Hong Kong, Shatin, Hong Kong.
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13
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Domschke K, Seuling PD, Schiele MA, Bandelow B, Batelaan NM, Bokma WA, Branchi I, Broich K, Burkauskas J, Davies SJC, Dell'Osso B, Fagan H, Fineberg NA, Furukawa TA, Hofmann SG, Hood S, Huneke NTM, Latas M, Lidbetter N, Masdrakis V, McAllister-Williams RH, Nardi AE, Pallanti S, Penninx BWJH, Perna G, Pilling S, Pini S, Reif A, Seedat S, Simons G, Srivastava S, Steibliene V, Stein DJ, Stein MB, van Ameringen M, van Balkom AJLM, van der Wee N, Zwanzger P, Baldwin DS. The definition of treatment resistance in anxiety disorders: a Delphi method-based consensus guideline. World Psychiatry 2024; 23:113-123. [PMID: 38214637 PMCID: PMC10785995 DOI: 10.1002/wps.21177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/13/2024] Open
Abstract
Anxiety disorders are very prevalent and often persistent mental disorders, with a considerable rate of treatment resistance which requires regulatory clinical trials of innovative therapeutic interventions. However, an explicit definition of treatment-resistant anxiety disorders (TR-AD) informing such trials is currently lacking. We used a Delphi method-based consensus approach to provide internationally agreed, consistent and clinically useful operational criteria for TR-AD in adults. Following a summary of the current state of knowledge based on international guidelines and an available systematic review, a survey of free-text responses to a 29-item questionnaire on relevant aspects of TR-AD, and an online consensus meeting, a panel of 36 multidisciplinary international experts and stakeholders voted anonymously on written statements in three survey rounds. Consensus was defined as ≥75% of the panel agreeing with a statement. The panel agreed on a set of 14 recommendations for the definition of TR-AD, providing detailed operational criteria for resistance to pharmacological and/or psychotherapeutic treatment, as well as a potential staging model. The panel also evaluated further aspects regarding epidemiological subgroups, comorbidities and biographical factors, the terminology of TR-AD vs. "difficult-to-treat" anxiety disorders, preferences and attitudes of persons with these disorders, and future research directions. This Delphi method-based consensus on operational criteria for TR-AD is expected to serve as a systematic, consistent and practical clinical guideline to aid in designing future mechanistic studies and facilitate clinical trials for regulatory purposes. This effort could ultimately lead to the development of more effective evidence-based stepped-care treatment algorithms for patients with anxiety disorders.
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Affiliation(s)
- Katharina Domschke
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Patrik D Seuling
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Miriam A Schiele
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Borwin Bandelow
- Department of Psychiatry and Psychotherapy, University Medical Center, Göttingen, Germany
| | - Neeltje M Batelaan
- Department of Psychiatry and Amsterdam Public Health Research Institute, Amsterdam University Medical Center, Vrije Universiteit, Amsterdam, The Netherlands
| | - Wicher A Bokma
- Department of Psychiatry and Amsterdam Public Health Research Institute, Amsterdam University Medical Center, Vrije Universiteit, Amsterdam, The Netherlands
| | - Igor Branchi
- Center for Behavioral Sciences and Mental Health, Istituto Superiore di Sanità, Rome, Italy
| | - Karl Broich
- Federal Institute for Drugs and Medical Devices, Bonn, Germany
| | - Julius Burkauskas
- Laboratory of Behavioral Medicine, Neuroscience Institute, Lithuanian University of Health Sciences, Palanga, Lithuania
| | - Simon J C Davies
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Bernardo Dell'Osso
- Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
- Department of Mental Health and Addictions, ASST Fatebenefratelli-Sacco, Milan, Italy
| | - Harry Fagan
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
- Southern Health NHS Foundation Trust, Southampton, UK
| | - Naomi A Fineberg
- University of Hertfordshire & Hertfordshire Partnership, University NHS Foundation Trust, Hatfield, UK
| | - Toshi A Furukawa
- Department of Health Promotion and Human Behavior, Kyoto University Graduate School of Medicine/School of Public Health, Kyoto, Japan
| | - Stefan G Hofmann
- Department of Clinical Psychology, Philipps University Marburg, Marburg, Germany
| | - Sean Hood
- Division of Psychiatry, Medical School, University of Western Australia, Perth, WA, Australia
| | - Nathan T M Huneke
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
- Southern Health NHS Foundation Trust, Southampton, UK
| | - Milan Latas
- Clinic for Psychiatry, University Clinical Center of Serbia, Belgrade, Serbia
- Belgrade University School of Medicine, Belgrade, Serbia
| | | | - Vasilios Masdrakis
- First Department of Psychiatry, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - R Hamish McAllister-Williams
- Translational and Clinical Research Institute, Newcastle University, Newcastle, UK
- Cumbria, Northumberland, Tyne & Wear NHS Foundation Trust, Newcastle, UK
| | - Antonio E Nardi
- Panic & Respiration Laboratory, Institute of Psychiatry, Medical School, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Stefano Pallanti
- Institute of Neuroscience, Florence, Italy
- Albert Einstein College of Medicine, New York, NY, USA
| | - Brenda W J H Penninx
- Department of Psychiatry and Amsterdam Public Health Research Institute, Amsterdam University Medical Center, Vrije Universiteit, Amsterdam, The Netherlands
| | - Giampaolo Perna
- Department of Biological Sciences, Humanitas University, Milan, Italy
| | - Steve Pilling
- Centre for Outcomes Research and Effectiveness, Research Department of Clinical, Educational & Health Psychology, University College London, London, UK
| | - Stefano Pini
- University of Pisa School of Medicine, Pisa, Italy
| | - Andreas Reif
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, Goethe University Frankfurt, Frankfurt am Main, Germany
- Fraunhofer Institute for Translational Medicine and Pharmacology, Frankfurt am Main, Germany
| | - Soraya Seedat
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Gemma Simons
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
- Solent NHS Trust, Southampton, UK
| | | | - Vesta Steibliene
- Neuroscience Institute and Clinic of Psychiatry, Faculty of Medicine, Lithuanian University of Health Sciences, Kaunas, Lithuania
| | - Dan J Stein
- South African Medical Research Council Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Murray B Stein
- Department of Psychiatry and School of Public Health, University of California San Diego, San Diego, CA, USA
| | - Michael van Ameringen
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
| | - Anton J L M van Balkom
- Department of Psychiatry and Amsterdam Public Health Research Institute, Amsterdam University Medical Center, Vrije Universiteit, Amsterdam, The Netherlands
| | - Nic van der Wee
- Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands
- Leiden Institute for Brain and Cognition, Leiden, The Netherlands
| | - Peter Zwanzger
- Clinical Center for Psychiatry, Psychotherapy and Psychosomatic Medicine, Kbo-Inn-Salzach Hospital, Wasserburg am Inn, Germany
- Department of Psychiatry and Psychotherapy, Ludwigs-Maximilians-University Munich, Munich, Germany
| | - David S Baldwin
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
- Southern Health NHS Foundation Trust, Southampton, UK
- South African Medical Research Council Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
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14
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Park J, Lee C, Nam YE, Lee H. Association between depressive symptoms and dynamic balance among young adults in the community. Heliyon 2024; 10:e24093. [PMID: 38293335 PMCID: PMC10826134 DOI: 10.1016/j.heliyon.2024.e24093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 12/11/2023] [Accepted: 01/03/2024] [Indexed: 02/01/2024] Open
Abstract
Background Detecting and addressing depression symptoms at their outset can reduce the burden on individuals and society; however, it has a limitation in that such evaluations mainly rely on self-reports. Several studies have demonstrated a strong association between motor symptoms and early depression. We aimed to associate body balance measured by the Lower Quarter Y Balance Test (YBT-LQ) with depressive symptoms among young adults in the community, to confirm the current evidence that depression negatively influences body balance. Research question Is the YBT-LQ an objective tool for measuring and evaluating young adults' depression risks, as well as assessing whether depression negatively influences body balance? Methods Our participants comprised 36 young adults. We assessed their depressive symptoms using the Center for Epidemiological Studies Depression Scale (CES-D) via a Google survey, measured their body balance with the YBT-LQ, and analyzed data with Spearman's rank-order correlation coefficient test, using SPSS version 27.0. Results We found that the right leg's anterior, posteromedial, and posterolateral scores- Z = -2.129, p = .033; Z = -2.181, p = .029; and Z = -2.250, p = .024, respectively-and composite scores-Z = 73.00, p = .027 -were significantly lower in the group with risk for clinical depression compared to the normal group. The CES-D total score had a negative association with all YBT-LQ scores, except for the anterior score of the left leg. Among the CES-D sub-factors, somatic and retarded activity showed negative correlations with all the YBT-LQ scores. Significance Our findings revealed that depressive symptoms have a negative association with balance, and that the YBT-LQ can be a reliable tool for measuring motor symptoms of depression, specifically among young adults.
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Affiliation(s)
- Jinyoung Park
- College of Nursing, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea
| | - Cynthia Lee
- School of Integrated Health Sciences, University of Nevada, Las Vegas (UNLV), 4505 S. Maryland Pkwy, Las Vegas, NV, 89154, USA
| | - Ye Eun Nam
- Kirk Kerkorian School of Medicine, University of Nevada, Las Vegas (UNLV), 625 Shadow Ln, Las Vegas, NV, 89128, USA
| | - Hyunhwa Lee
- School of Nursing, University of Nevada, Las Vegas (UNLV), 4505 S. Maryland Pkwy., Las Vegas, NV, 89154, USA
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15
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Chatterjee S, Mishra J, Sundram F, Roop P. Towards Personalised Mood Prediction and Explanation for Depression from Biophysical Data. SENSORS (BASEL, SWITZERLAND) 2023; 24:164. [PMID: 38203024 PMCID: PMC10781272 DOI: 10.3390/s24010164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 11/30/2023] [Accepted: 12/19/2023] [Indexed: 01/12/2024]
Abstract
Digital health applications using Artificial Intelligence (AI) are a promising opportunity to address the widening gap between available resources and mental health needs globally. Increasingly, passively acquired data from wearables are augmented with carefully selected active data from depressed individuals to develop Machine Learning (ML) models of depression based on mood scores. However, most ML models are black box in nature, and hence the outputs are not explainable. Depression is also multimodal, and the reasons for depression may vary significantly between individuals. Explainable and personalised models will thus be beneficial to clinicians to determine the main features that lead to a decline in the mood state of a depressed individual, thus enabling suitable personalised therapy. This is currently lacking. Therefore, this study presents a methodology for developing personalised and accurate Deep Learning (DL)-based predictive mood models for depression, along with novel methods for identifying the key facets that lead to the exacerbation of depressive symptoms. We illustrate our approach by using an existing multimodal dataset containing longitudinal Ecological Momentary Assessments of depression, lifestyle data from wearables and neurocognitive assessments for 14 mild to moderately depressed participants over one month. We develop classification- and regression-based DL models to predict participants' current mood scores-a discrete score given to a participant based on the severity of their depressive symptoms. The models are trained inside eight different evolutionary-algorithm-based optimisation schemes that optimise the model parameters for a maximum predictive performance. A five-fold cross-validation scheme is used to verify the DL model's predictive performance against 10 classical ML-based models, with a model error as low as 6% for some participants. We use the best model from the optimisation process to extract indicators, using SHAP, ALE and Anchors from explainable AI literature to explain why certain predictions are made and how they affect mood. These feature insights can assist health professionals in incorporating personalised interventions into a depressed individual's treatment regimen.
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Affiliation(s)
- Sobhan Chatterjee
- Department of Electrical, Computer and Software Engineering, Faculty of Engineering, University of Auckland, Auckland 1010, New Zealand
| | - Jyoti Mishra
- Neural Engineering and Translation Labs, Department of Psychiatry, University of California, San Diego, CA 92093, USA;
| | - Frederick Sundram
- Department of Psychological Medicine, Faculty of Medical and Health Sciences, University of Auckland, Auckland 1023, New Zealand;
| | - Partha Roop
- Department of Electrical, Computer and Software Engineering, Faculty of Engineering, University of Auckland, Auckland 1010, New Zealand
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16
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Chen AA, Weinstein SM, Adebimpe A, Gur RC, Gur RE, Merikangas KR, Satterthwaite TD, Shinohara RT, Shou H. Similarity-based multimodal regression. Biostatistics 2023:kxad033. [PMID: 38058018 DOI: 10.1093/biostatistics/kxad033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 10/07/2023] [Accepted: 11/06/2023] [Indexed: 12/08/2023] Open
Abstract
To better understand complex human phenotypes, large-scale studies have increasingly collected multiple data modalities across domains such as imaging, mobile health, and physical activity. The properties of each data type often differ substantially and require either separate analyses or extensive processing to obtain comparable features for a combined analysis. Multimodal data fusion enables certain analyses on matrix-valued and vector-valued data, but it generally cannot integrate modalities of different dimensions and data structures. For a single data modality, multivariate distance matrix regression provides a distance-based framework for regression accommodating a wide range of data types. However, no distance-based method exists to handle multiple complementary types of data. We propose a novel distance-based regression model, which we refer to as Similarity-based Multimodal Regression (SiMMR), that enables simultaneous regression of multiple modalities through their distance profiles. We demonstrate through simulation, imaging studies, and longitudinal mobile health analyses that our proposed method can detect associations between clinical variables and multimodal data of differing properties and dimensionalities, even with modest sample sizes. We perform experiments to evaluate several different test statistics and provide recommendations for applying our method across a broad range of scenarios.
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Affiliation(s)
- Andrew A Chen
- Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC 29425, USA
| | - Sarah M Weinstein
- Department of Epidemiology and Biostatistics, Temple University College of Public Health, Philadelphia, PA 19122, USA
| | - Azeez Adebimpe
- Penn Lifespan Informatics & Neuroimaging Center, Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Ruben C Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Raquel E Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Kathleen R Merikangas
- Genetic Epidemiology Research Branch, Intramural Research Program, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Theodore D Satterthwaite
- Penn Lifespan Informatics & Neuroimaging Center, Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Russell T Shinohara
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Haochang Shou
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA 19104, USA
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17
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Urben S, Constanty L, Lepage C, Rosselet Amoussou J, Durussel J, Turri F, Wouters E, Mürner-Lavanchy I, Plessen KJ. The added value of a micro-level ecological approach when mapping self-regulatory control processes and externalizing symptoms during adolescence: a systematic review. Eur Child Adolesc Psychiatry 2023; 32:2387-2397. [PMID: 35294631 PMCID: PMC10682160 DOI: 10.1007/s00787-022-01972-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Accepted: 03/03/2022] [Indexed: 11/03/2022]
Abstract
Deficits in self-regulatory control (SRC) represent a core characteristic of externalizing (EXT) symptoms (e.g., rule-breaking behavior or aggressive behaviors) in adolescents. This review aims to specify the added value of ecologically valid assessments at a micro-level when examining the associations between SRC and EXT symptoms in adolescents. This systematic review was reported according to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) 2020. The search strategy addressed the added value of (1) naturalistic assessment for the understanding of the relationship between (2) SRC and (3) EXT symptoms in (4) adolescents. We conducted comprehensive searches in bibliographic databases. An additional search was conducted in Google Scholar and supplementary studies were identified through backward and forward citation tracking. Twenty-four studies (n = 4071 adolescents) met the inclusion criteria. The methods used to assess naturalistic aspects included the experience sampling method (ecological momentary- or ambulatory assessment) and the time-course approach (i.e., real-time assessment of SRC processes referring to situations approximating real-life experience where SRC are to be engaged such as in frustrating situations). Micro-level ecological assessments, when mapping the intra-individual relationships between SRC processes and EXT symptoms over time in adolescents within their natural context (i.e., real world) of expression in real time, added a finer-grained observation alongside with a higher ecological validity. Micro-level approaches may enhance the understanding of the complex interplay between SRC and EXT symptoms in adolescence, especially in interventional studies, allowing for the acquisition of endpoints with a higher relevance for everyday functioning.
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Affiliation(s)
- Sébastien Urben
- Division of Child and Adolescent Psychiatry, Department of Psychiatry, Lausanne University Hospital (CHUV), University of Lausanne, Lausanne, Switzerland.
| | - Lauriane Constanty
- Division of Child and Adolescent Psychiatry, Department of Psychiatry, Lausanne University Hospital (CHUV), University of Lausanne, Lausanne, Switzerland
| | - Caroline Lepage
- Division of Child and Adolescent Psychiatry, Department of Psychiatry, Lausanne University Hospital (CHUV), University of Lausanne, Lausanne, Switzerland
| | - Joëlle Rosselet Amoussou
- Psychiatry Library, Education and Research Department, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland
| | - Julie Durussel
- Division of Child and Adolescent Psychiatry, Department of Psychiatry, Lausanne University Hospital (CHUV), University of Lausanne, Lausanne, Switzerland
| | - Fiorella Turri
- Division of Child and Adolescent Psychiatry, Department of Psychiatry, Lausanne University Hospital (CHUV), University of Lausanne, Lausanne, Switzerland
| | - Emilie Wouters
- Unit of Child and Adolescent Forensic Psychiatry, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Ines Mürner-Lavanchy
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Kerstin Jessica Plessen
- Division of Child and Adolescent Psychiatry, Department of Psychiatry, Lausanne University Hospital (CHUV), University of Lausanne, Lausanne, Switzerland
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18
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Stapp EK, Zipunnikov V, Leroux A, Cui L, Husky MM, Dey D, Merikangas KR. Specificity of affective dynamics of bipolar and major depressive disorder. Brain Behav 2023; 13:e3134. [PMID: 37574463 PMCID: PMC10498074 DOI: 10.1002/brb3.3134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 05/10/2023] [Accepted: 06/08/2023] [Indexed: 08/15/2023] Open
Abstract
OBJECTIVE Here, we examine whether the dynamics of the four dimensions of the circumplex model of affect assessed by ecological momentary assessment (EMA) differ among those with bipolar disorder (BD) and major depressive disorder (MDD). METHODS Participants aged 11-85 years (n = 362) reported momentary sad, anxious, active, and energetic dimensional states four times per day for 2 weeks. Individuals with lifetime mood disorder subtypes of bipolar-I, bipolar-II, and MDD derived from a semistructured clinical interview were compared to each other and to controls without a lifetime history of psychiatric disorders. Random effects from individual means, inertias, innovation (residual) variances, and cross-lags across the four affective dimensions simultaneously were derived from multivariate dynamic structural equation models. RESULTS All mood disorder subtypes were associated with higher levels of sad and anxious mood and lower energy than controls. Those with bipolar-I had lower average activation, and lower energy that was independent of activation, compared to MDD or controls. However, increases in activation were more likely to perpetuate in those with bipolar-I. Bipolar-II was characterized by higher lability of sad and anxious mood compared to bipolar-I and controls but not MDD. Compared to BD and controls, those with MDD exhibited cross-augmentation of sadness and anxiety, and sadness blunted energy. CONCLUSION Bipolar-I is more strongly characterized by activation and energy than sad and anxious mood. This distinction has potential implications for both specificity of intervention targets and differential pathways underlying these dynamic affective systems. Confirmation of the longer term stability and generalizability of these findings in future studies is necessary.
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Affiliation(s)
- Emma K. Stapp
- Genetic Epidemiology Research BranchNational Institute of Mental HealthBethesdaMarylandUSA
- Department of Epidemiology, Milken Institute School of Public HealthGeorge Washington UniversityWashington, D.C.USA
| | - Vadim Zipunnikov
- Department of BiostatisticsJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
| | - Andrew Leroux
- Department of Biostatistics and InformaticsUniversity of Colorado School of Public HealthAuroraColoradoUSA
| | - Lihong Cui
- Genetic Epidemiology Research BranchNational Institute of Mental HealthBethesdaMarylandUSA
| | - Mathilde M. Husky
- Bordeaux Population Health Research CenterUniversity of BordeauxBordeauxFrance
| | - Debangan Dey
- Genetic Epidemiology Research BranchNational Institute of Mental HealthBethesdaMarylandUSA
| | - Kathleen R. Merikangas
- Genetic Epidemiology Research BranchNational Institute of Mental HealthBethesdaMarylandUSA
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19
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Conway KP, McGrain P, Theodory M. Fell on Black Days: Analyzing the Song Lyrics of Chris Cornell for Insight into Depression and Suicide. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:6621. [PMID: 37623204 PMCID: PMC10454542 DOI: 10.3390/ijerph20166621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 07/31/2023] [Accepted: 08/17/2023] [Indexed: 08/26/2023]
Abstract
Chris Cornell was a guitarist, singer, songwriter, and pioneer of grunge music. Cornell struggled with mental illness and addiction and incorporated these themes into his song lyrics. At age 52, Cornell died by suicide in his hotel bathroom following a live performance. This mixed-methods study examines Cornell's song lyrics for references to negative words and themes related to depression and suicide. Two coders independently reviewed lyrical transcripts to identify the primary theme, secondary theme(s), and valence (positive or negative). Sentiment analysis, a natural language processing technique, was used to examine word frequency and valence. Songs (N = 215) were predominantly (79%) negative and contained more negative (N = 3244, 56.1%) than positive (N = 2537, 43.9%) words. Thematic analysis by stage of career shows a narrowing focus on depression, failed relationships, and morbid thoughts. Themes of depressed mood, death, and suicide were common and increased by stage of career. By applying qualitative and quantitative techniques to song lyrics, this study revealed that Cornell's songs reflect a narrative of negativity consistent with someone experiencing depression and thoughts of death and suicide. Like personal notes and poems, song lyrics may reflect symptoms of depression and suicidal thoughts warranting clinical attention.
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Affiliation(s)
- Kevin P. Conway
- Genetic Epidemiology Research Branch, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Patrick McGrain
- Department of Criminal Justice, Gwynedd Mercy University, Gwynedd Valley, PA 19437, USA;
| | - Michelle Theodory
- Department of Biomedical Informatics, Harvard University, Boston, MA 02115, USA;
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20
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Pernold K, Rullman E, Ulfhake B. Bouts of rest and physical activity in C57BL/6J mice. PLoS One 2023; 18:e0280416. [PMID: 37363906 DOI: 10.1371/journal.pone.0280416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Accepted: 06/05/2023] [Indexed: 06/28/2023] Open
Abstract
The objective was to exploit the raw data output from a scalable home cage (type IIL IVC) monitoring (HCM) system (DVC®), to characterize pattern of undisrupted rest and physical activity (PA) of C57BL/6J mice. The system's tracking algorithm show that mice in isolation spend 67% of the time in bouts of long rest (≥40s). Sixteen percent is physical activity (PA), split between local movements (6%) and locomotion (10%). Decomposition revealed that a day contains ˜7100 discrete bouts of short and long rest, local and locomotor movements. Mice travel ˜330m per day, mainly during the dark hours, while travelling speed is similar through the light-dark cycle. Locomotor bouts are usually <0.2m and <1% are >1m. Tracking revealed also fits of abnormal behaviour. The starting positions of the bouts showed no preference for the rear over the front of the cage floor, while there was a strong bias for the peripheral (75%) over the central floor area. The composition of bouts has a characteristic circadian pattern, however, intrusive husbandry routines increased bout fragmentation by ˜40%. Extracting electrode activations density (EAD) from the raw data yielded results close to those obtained with the tracking algorithm, with 81% of time in rest (<1 EAD s-1) and 19% in PA. Periods ≥40 s of file when no movement occurs and there is no EAD may correspond to periods of sleep (˜59% of file time). We confirm that EAD correlates closely with movement distance (rs>0.95) and the data agreed in ˜97% of the file time. Thus, albeit EAD being less informative it may serve as a proxy for PA and rest, enabling monitoring group housed mice. The data show that increasing density from one female to two males, and further to three male or female mice had the same effect size on EAD (˜2). In contrast, the EAD deviated significantly from this stepwise increase with 4 mice per cage, suggesting a crowdedness stress inducing sex specific adaptations. We conclude that informative metrics on rest and PA can be automatically extracted from the raw data flow in near-real time (< 1 hrs). As discussed, these metrics relay useful longitudinal information to those that use or care for the animals.
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Affiliation(s)
- Karin Pernold
- Division of Clinical Physiology, Department of Laboratory Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Eric Rullman
- Division of Clinical Physiology, Department of Laboratory Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Brun Ulfhake
- Division of Clinical Physiology, Department of Laboratory Medicine, Karolinska Institutet, Stockholm, Sweden
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21
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Zhang Y, Deng X, Wang X, Luo H, Lei X, Luo Q. Can daily actigraphic profiles distinguish between different mood states in inpatients with bipolar disorder? An observational study. Front Psychiatry 2023; 14:1145964. [PMID: 37363166 PMCID: PMC10287980 DOI: 10.3389/fpsyt.2023.1145964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Accepted: 05/18/2023] [Indexed: 06/28/2023] Open
Abstract
Background Criterion A changes for bipolar disorder (BD) in the Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition yield new difficulties in diagnosis. Actigraphy has been used to capture the activity features of patients with BD. However, it remains unclear whether long-term actigraphic data could distinguish between different mood states in hospitalized patients with BD. Methods In this observational study, 30 hospitalized patients with BD were included. Wrist-worn actigraphs were used to monitor motor activity. The patients were divided into bipolar disorder-depression (BD-D), bipolar disorder-mania (BD-M), and bipolar disorder-mixed state (BD-MS) groups. Motor activity differences were estimated using non-parametric analyses between and within the three groups. Results The mean 24 h activity level differed between the groups. In the between-group analysis, the intra-individual fluctuation and minute-to-minute variability in the morning and the mean activity level and minute-to-minute variability in the evening significantly differed between the BD-M and BD-MS groups. In the within-group analysis, the BD-M group showed a disrupted rhythm and reduced activity complexity at night. Both the BD-D and BD-MS groups demonstrated significant differences between several parameters obtained in the morning and evening. Conclusion The mean activity levels during the relatively long monitoring period and the intra-day variation within the groups could reflect the differences in motor activity. Sustained activity monitoring may clarify the emotional states and provide information for clinical diagnosis.
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Affiliation(s)
- Yinlin Zhang
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Xinyi Deng
- Sleep and Neuroimaging Center, Faculty of Psychology, Southwest University, Chongqing, China
| | - Xueqian Wang
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Huirong Luo
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Xu Lei
- Sleep and Neuroimaging Center, Faculty of Psychology, Southwest University, Chongqing, China
- Key Laboratory of Cognition and Personality, Ministry of Education, Southwest University, Chongqing, China
| | - Qinghua Luo
- Department of Psychiatry, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
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22
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Faurholt-Jepsen M, Busk J, Bardram JE, Stanislaus S, Frost M, Christensen EM, Vinberg M, Kessing LV. Mood instability and activity/energy instability in patients with bipolar disorder according to day-to-day smartphone-based data - An exploratory post hoc study. J Affect Disord 2023; 334:83-91. [PMID: 37149047 DOI: 10.1016/j.jad.2023.04.139] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 04/21/2023] [Accepted: 04/29/2023] [Indexed: 05/08/2023]
Abstract
BACKGROUND Alterations and instability in mood and activity/energy has been associated with impaired functioning and risk of relapse in bipolar disorder. The present study aimed to investigate whether mood instability and activity/energy instability are associated, and whether these instability measures are associated with stress, quality of life and functioning in patients with bipolar disorder. METHODS Data from two studies were combined for exploratory post hoc analyses. Patients with bipolar disorder provided smartphone-based evaluations of mood and activity/energy levels from day-to-day. In addition, information on functioning, perceived stress and quality of life was collected. A total of 316 patients with bipolar disorder were included. RESULTS A total of 55,968 observations of patient-reported smartphone-based data collected from day-to-day were available. Regardless of the affective state, there was a statistically significant positive association between mood instability and activity/energy instability in all models (all p-values < 0.0001). There was a statistically significant association between mood and activity/energy instability with patient-reported stress and quality of life (e.g., mood instability and stress: B: 0.098, 95 % CI: 0.085; 0.11, p < 0.0001), and between mood instability and functioning (B: 0.045, 95 % CI: 0.0011; 0.0080, p = 0.010). LIMITATIONS Findings should be interpreted with caution since the analyses were exploratory and post hoc by nature. CONCLUSION Mood instability and activity/energy instability is suggested to play important roles in the symptomatology of bipolar disorder. This highlight that monitoring and identifying subsyndromal inter-episodic fluctuations in symptoms is clinically recommended. Future studies investigating the effect of treatment on these measures would be interesting.
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Affiliation(s)
- Maria Faurholt-Jepsen
- Copenhagen Affective Disorder Research Center (CADIC), Psychiatric Center Copenhagen, Rigshospitalet, Copenhagen, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark.
| | - Jonas Busk
- Department of Energy Conversion and Storage, Technical University of Denmark, Lyngby, Denmark
| | - Jakob Eyvind Bardram
- Department of Health Technology, Technical University of Denmark, Lyngby, Denmark
| | - Sharleny Stanislaus
- Copenhagen Affective Disorder Research Center (CADIC), Psychiatric Center Copenhagen, Rigshospitalet, Copenhagen, Denmark
| | | | - Ellen Margrethe Christensen
- Copenhagen Affective Disorder Research Center (CADIC), Psychiatric Center Copenhagen, Rigshospitalet, Copenhagen, Denmark
| | - Maj Vinberg
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark; Mental Health Centre, Northern Zealand, Copenhagen University Hospital - Mental Health Services CPH, Copenhagen, Denmark
| | - Lars Vedel Kessing
- Copenhagen Affective Disorder Research Center (CADIC), Psychiatric Center Copenhagen, Rigshospitalet, Copenhagen, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
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23
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Mayeli A, LaGoy AD, Smagula SF, Wilson JD, Zarbo C, Rocchetti M, Starace F, Zamparini M, Casiraghi L, Calza S, Rota M, D'Agostino A, de Girolamo G, Ferrarelli F. Shared and distinct abnormalities in sleep-wake patterns and their relationship with the negative symptoms of Schizophrenia Spectrum Disorder patients. Mol Psychiatry 2023; 28:2049-2057. [PMID: 37055512 DOI: 10.1038/s41380-023-02050-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 03/21/2023] [Accepted: 03/23/2023] [Indexed: 04/15/2023]
Abstract
Sleep and rest-activity-rhythm (RAR) abnormalities are commonly reported in schizophrenia spectrum disorder (SSD) patients. However, an in-depth characterization of sleep/RAR alterations in SSD, including patients in different treatment settings, and the relationship between these alterations and SSD clinical features (e.g., negative symptoms) is lacking. SSD (N = 137 altogether, N = 79 residential and N = 58 outpatients) and healthy control (HC) subjects (N = 113) were recruited for the DiAPAson project. Participants wore an ActiGraph for seven consecutive days to monitor habitual sleep-RAR patterns. Sleep/rest duration, activity (i.e., M10, calculated on the 10 most active hours), rhythm fragmentation within days (i.e., intra-daily variability, IV; beta, steepness of rest-active changes), and rhythm regularity across days (i.e., inter-daily stability, IS) were computed in each study participant. Negative symptoms were assessed in SSD patients with the Brief Negative Symptom Scale (BNSS). Both SSD groups showed lower M10 and longer sleep/rest duration vs. HC, while only residential patients had more fragmented and irregular rhythms than HC. Compared to outpatients, residential patients had lower M10 and higher beta, IV and IS. Furthermore, residential patients had worse BNSS scores relative to outpatients, and higher IS contributed to between-group differences in BNSS score severity. Altogether, residentials and outpatients SSD had both shared and unique abnormalities in Sleep/RAR measures vs. HC and relative to one another, which also contributed to the patients' negative symptom severity. Future work will help establish whether improving some of these measures may ameliorate the quality of life and clinical symptoms of SSD patients.
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Affiliation(s)
- Ahmad Mayeli
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Alice D LaGoy
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Stephen F Smagula
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - James D Wilson
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Cristina Zarbo
- Unit of Epidemiological Psychiatry and Evaluation, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Matteo Rocchetti
- Department of Mental Health and Dependence, ASST of Pavia, Pavia, Italy
| | - Fabrizio Starace
- Department of Mental Health and Dependence, AUSL of Modena, Modena, Italy
| | - Manuel Zamparini
- Unit of Epidemiological Psychiatry and Evaluation, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Letizia Casiraghi
- Department of Mental Health and Dependence, ASST of Pavia, Pavia, Italy
| | - Stefano Calza
- Unit of Biostatistics and Bioinformatics, Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Matteo Rota
- Unit of Biostatistics and Bioinformatics, Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | | | - Giovanni de Girolamo
- Unit of Epidemiological Psychiatry and Evaluation, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Fabio Ferrarelli
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.
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Hickie IB, Merikangas KR, Carpenter JS, Iorfino F, Scott EM, Scott J, Crouse JJ. Does circadian dysrhythmia drive the switch into high- or low-activation states in bipolar I disorder? Bipolar Disord 2023; 25:191-199. [PMID: 36661342 PMCID: PMC10947388 DOI: 10.1111/bdi.13304] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
OBJECTIVES Emerging evidence suggests a role of circadian dysrhythmia in the switch between "activation" states (i.e., objective motor activity and subjective energy) in bipolar I disorder. METHODS We examined the evidence with respect to four relevant questions: (1) Are natural or environmental exposures that can disrupt circadian rhythms also related to the switch into high-/low-activation states? (2) Are circadian dysrhythmias (e.g., altered rest/activity rhythms) associated with the switch into activation states in bipolar disorder? (3) Do interventions that affect the circadian system also affect activation states? (4) Are associations between circadian dysrhythmias and activation states influenced by other "third" factors? RESULTS Factors that naturally or experimentally alter circadian rhythms (e.g., light exposure) have been shown to relate to activation states; however future studies need to measure circadian rhythms contemporaneously with these natural/experimental factors. Actigraphic measures of circadian dysrhythmias are associated prospectively with the switch into high- or low-activation states, and more studies are needed to establish the most relevant prognostic actigraphy metrics in bipolar disorder. Interventions that can affect the circadian system (e.g., light therapy, lithium) can also reduce the switch into high-/low-activation states. Whether circadian rhythms mediate these clinical effects is an unknown but valuable question. The influence of age, sex, and other confounders on these associations needs to be better characterised. CONCLUSION Based on the reviewed evidence, our view is that circadian dysrhythmia is a plausible driver of transitions into high- and low-activation states and deserves prioritisation in research in bipolar disorders.
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Affiliation(s)
- Ian B. Hickie
- Youth Mental Health and Technology Team, Brain and Mind Centre, Faculty of Medicine and HealthUniversity of SydneyNew South WalesSydneyAustralia
| | - Kathleen R. Merikangas
- Genetic Epidemiology Research Branch, Division of Intramural Research ProgramNational Institute of Mental HealthBethesdaMarylandUSA
| | - Joanne S. Carpenter
- Youth Mental Health and Technology Team, Brain and Mind Centre, Faculty of Medicine and HealthUniversity of SydneyNew South WalesSydneyAustralia
| | - Frank Iorfino
- Youth Mental Health and Technology Team, Brain and Mind Centre, Faculty of Medicine and HealthUniversity of SydneyNew South WalesSydneyAustralia
| | - Elizabeth M. Scott
- Youth Mental Health and Technology Team, Brain and Mind Centre, Faculty of Medicine and HealthUniversity of SydneyNew South WalesSydneyAustralia
| | - Jan Scott
- Institute of NeuroscienceNewcastle UniversityNewcastle upon TyneUK
- Norwegian University of Science and TechnologyTrondheimNorway
- Université de ParisParisFrance
| | - Jacob J. Crouse
- Youth Mental Health and Technology Team, Brain and Mind Centre, Faculty of Medicine and HealthUniversity of SydneyNew South WalesSydneyAustralia
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25
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Anmella G, Corponi F, Li BM, Mas A, Sanabra M, Pacchiarotti I, Valentí M, Grande I, Benabarre A, Giménez-Palomo A, Garriga M, Agasi I, Bastidas A, Cavero M, Fernández-Plaza T, Arbelo N, Bioque M, García-Rizo C, Verdolini N, Madero S, Murru A, Amoretti S, Martínez-Aran A, Ruiz V, Fico G, De Prisco M, Oliva V, Solanes A, Radua J, Samalin L, Young AH, Vieta E, Vergari A, Hidalgo-Mazzei D. Exploring digital biomarkers of illness activity in mood episodes: hypotheses generating and model development study. JMIR Mhealth Uhealth 2023; 11:e45405. [PMID: 36939345 DOI: 10.2196/45405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 02/20/2023] [Accepted: 03/07/2023] [Indexed: 03/21/2023] Open
Abstract
BACKGROUND Depressive and manic episodes within bipolar disorder (BD) and major depressive disorder (MDD) involve altered mood, sleep, and activity alongside physiological alterations that wearables can capture. OBJECTIVE We explored whether physiological wearable data could predict: (aim 1) the severity of an acute affective episode at the intra-individual level, (aim 2) the polarity of an acute affective episode and euthymia among different individuals. Secondarily, we explored which physiological data were related to the prior predictions, generalization across patients, and associations between affective symptoms and physiological data. METHODS We conducted a prospective exploratory observational study including patients with BD and MDD on acute affective episodes (manic, depressed, and mixed) whose physiological data were recorded with a research-grade wearable (Empatica E4) across three consecutive timepoints (acute, response, and remission of episode). Euthymic patients and healthy controls (HC) were recorded during a single session (∼48 hours). Manic and depressive symptoms were assessed with standardized psychometric scales. Physiological wearable data included the following channels: acceleration (ACC), temperature (TEMP), blood volume pulse (BVP), heart rate (HR), and electrodermal activity (EDA). For data pre-processing, invalid physiological data were removed using a rule-based filter, channels were time-aligned at 1 second time units and then segmented window lengths of 32 seconds, since those parameters showed the best performances. We developed deep learning predictive models, assessed channels' individual contribution using permutation feature importance analysis, and computed physiological data to psychometric scales' items normalized mutual information (NMI). We present a novel fully automated method for analysis of physiological data from a research-grade wearable device, including a rule-based filter for invalid data and a viable supervised learning pipeline for time-series analyses. RESULTS 35 sessions (1,512 hours) from 12 patients (manic, depressed, mixed, and euthymic) and 7 HC (age 39.7±12.6; 31.6% female) were analyzed. (aim 1) The severity of mood episodes was predicted with moderate (62%-85%) accuracies. (aim 2) The polarity of episodes was predicted with moderate (70%) accuracy. The most relevant features for the former tasks were ACC, EDA, and HR. Kendall W showed fair agreement (0.383) in feature importance across classification tasks. Generalization of the former models were of overall low accuracy, with better results for the intra-individual models. "Increased motor activity" was associated with ACC (NMI>0.55), "aggressive behavior" with EDA (NMI=1.0), "insomnia" with ACC (NMI∼0.6), "motor inhibition" with ACC (NMI∼0.75), and "psychic anxiety" with EDA (NMI=0.52). CONCLUSIONS Physiological data from wearables show potential to identify mood episodes and specific symptoms of mania and depression quantitatively, both in BD and MDD. Motor activity and stress-related physiological data (EDA and HR) stand out as potential digital biomarkers for predicting mania and depression respectively. These findings represent a promising pathway towards personalized psychiatry, in which physiological wearable data could allow early identification and intervention of mood episodes. CLINICALTRIAL
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Affiliation(s)
- Gerard Anmella
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Filippo Corponi
- School of informatics, University of Edinburgh, UK., Edinburgh, GB
| | - Bryan M Li
- School of informatics, University of Edinburgh, UK., Edinburgh, GB
| | - Ariadna Mas
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Miriam Sanabra
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Isabella Pacchiarotti
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Marc Valentí
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Iria Grande
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Antoni Benabarre
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Anna Giménez-Palomo
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Marina Garriga
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Isabel Agasi
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Anna Bastidas
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Myriam Cavero
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | | | - Néstor Arbelo
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Miquel Bioque
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Clemente García-Rizo
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Norma Verdolini
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Santiago Madero
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Andrea Murru
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Silvia Amoretti
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Anabel Martínez-Aran
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Victoria Ruiz
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Giovanna Fico
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Michele De Prisco
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Vincenzo Oliva
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Aleix Solanes
- Imaging of Mood- and Anxiety-Related Disorders (IMARD) group, Barcelona, ES
| | - Joaquim Radua
- Imaging of Mood- and Anxiety-Related Disorders (IMARD) group, Barcelona, ES
| | - Ludovic Samalin
- Department of Psychiatry, CHU Clermont-Ferrand, University of Clermont Auvergne, CNRS, Clermont Auvergne INP, Institut Pascal (UMR 6602), Clermont-Ferrand, France., Clermont-Ferrand, FR
| | - Allan H Young
- Centre for Affective Disorders, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom., London, GB
| | - Eduard Vieta
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
| | - Antonio Vergari
- School of informatics, University of Edinburgh, UK., Edinburgh, GB
| | - Diego Hidalgo-Mazzei
- Hospital Clínic de Barcelona, Villarroel St., 170, 08036 Barcelona, Spain., Barcelona, ES
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Wu C, Li W, Cen D, Zhou Q. Is insufficient sleep duration a risk indicator for periodontal disease? A systematic review. Int J Dent Hyg 2023; 21:18-27. [PMID: 36385732 DOI: 10.1111/idh.12633] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2021] [Revised: 08/15/2022] [Accepted: 10/24/2022] [Indexed: 11/19/2022]
Abstract
OBJECTIVES In this study, we conducted a systematic review and meta-analysis to assess whether people who achieved <7 h of sleep were more likely to develop periodontal disease (PD). SOURCES We executed electronic searches in the PubMed, EMBASE and Cochrane Library, as well as a manual search of articles published by leading journals in related fields, for observational studies, published in English from 1 January 1966 to 31 March 2021.which evaluated the relationship between sleep duration and PD. The Agency for Healthcare Research and Quality (AHRQ) quality evaluation scale was used for the cross-sectional studies, and the random effects model was used to summarize the effect sizes in the included studies with a 95% confidence interval (CI). RESULTS A total of six cross-sectional studies met the inclusion criteria, totaling 107,777 participants, of which 69,773 had PD. The results of the present indicated that shorter sleep duration (<7 h) is significantly associated with PD (Odd ratio [OR], 1.19; 95% CI, 1.16-1.23; p < 0.001; I2 , 0.0%, I2 interval, 0%-75%). The strength of the sensitivity analysis and cumulative meta-analysis confirmed the reliability of the results. CONCLUSION Although the inclusion of only six studies makes it difficult to explore whether there is a publication bias, we found that insufficient sleep duration was closely related to PD, and we therefore speculated that getting enough sleep may help prevent PD.
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Affiliation(s)
- Chuanbin Wu
- School and Hospital of Stomatology, China Medical University, Shenyang, China
| | - Weiqi Li
- School and Hospital of Stomatology, China Medical University, Shenyang, China.,Liaoning Province Key Laboratory of Oral Diseases, Shenyang, China
| | - Dongdong Cen
- School and Hospital of Stomatology, China Medical University, Shenyang, China
| | - Qing Zhou
- School and Hospital of Stomatology, China Medical University, Shenyang, China
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Hong S, Lee S, Song K, Kim M, Kim Y, Kim H, Kim H. A nurse-led mHealth intervention to alleviate depressive symptoms in older adults living alone in the community: A quasi-experimental study. Int J Nurs Stud 2023; 138:104431. [PMID: 36630872 DOI: 10.1016/j.ijnurstu.2022.104431] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 12/04/2022] [Accepted: 12/13/2022] [Indexed: 12/23/2022]
Abstract
BACKGROUND The prevalence of geriatric depression has increased worldwide, becoming a major contributor to the burden of health care costs. Geriatric depression is difficult to detect in daily life because of its atypical presentation for each person. Therefore, there is an emerging need to develop personalised mHealth interventions for older adults with depression based on data from an ecological momentary assessment. OBJECTIVE To develop and evaluate the effect of a nurse-led mHealth intervention of geriatric depression in older adults living alone. DESIGN A quasi-experimental research design was used, and the study followed the transparent reporting of evaluations with a nonrandomised design statement. SETTING The nurse-led mHealth intervention was developed and evaluated in a community senior centre in Seoul, Korea. PARTICIPANTS Sixty-four older adults living alone with depressive symptoms were recruited between 1 October 2018 and 1 October 2019. METHODS Study participants were randomly assigned to the intervention or control groups by drawing lots. In the intervention group, nurses repeatedly assessed older adults' depressive symptoms using an ecological momentary assessment via a mobile tablet. The intervention consisted of weekly sessions, which included (1) standardised mHealth device training, (2) a nurse-led mHealth programme, and (3) art activities. The control group received care as usual. Intra- and inter-group differences were evaluated using paired t-tests and analysis of covariance was used to assess subjective depression symptoms. A linear mixed-model was used to analyse the relationship between groups and momentary scores over time. RESULTS The average age of the final sample was 76.2 years (SD = 6.06), 63.6 % (28/44) of whom were female. Compared with the control group (n = 23), the intervention group (n = 21) showed a decreased depression score (t = 4.041, p = .027). There was no statistical difference between the intervention and control groups based on traditional scales and the ecological momentary assessment. However, our data from the ecological momentary assessment captures clear fluctuating patterns across the days during the study, which traditional scales could not measure. CONCLUSIONS Most of the older adults successfully participated in a nurse-led mHealth intervention that included multiple components of a non-pharmacological approach to address depression. Mental health nurses should perform critical roles to personalise mHealth activities considering the older adult's autonomy and supportive decision-making, specifically when using high-technological intervention. Future research should maximise the methodological and clinical advantage of an ecological momentary assessment of geriatric depression. REGISTRATION Clinical Research Information Service number KCT0005073.
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Affiliation(s)
- Soyun Hong
- College of Nursing Brain Korea 21 FOUR Project, Yonsei University, Seoul, Republic of Korea; College of Nursing, Namseoul University, Cheonan-si, Republic of Korea
| | - Sangeun Lee
- College of Nursing, University of Illinois at Chicago, Chicago, United States
| | - Kijun Song
- College of Nursing and Mo-Im Kim Nursing Research Institute, Yonsei University, Seoul, Republic of Korea
| | - Mijung Kim
- Mapo Senior Welfare Center, Seoul, Republic of Korea
| | - Yuntae Kim
- Mapo Senior Welfare Center, Seoul, Republic of Korea
| | - Hyein Kim
- College of Nursing Brain Korea 21 FOUR Project, Yonsei University, Seoul, Republic of Korea
| | - Heejung Kim
- College of Nursing and Mo-Im Kim Nursing Research Institute, Yonsei University, Seoul, Republic of Korea.
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Dalkner N, Moore RC, Depp CA, Ackerman RA, Pinkham AE, Harvey PD. Negative mood states as a correlate of cognitive performance and self-assessment of cognitive performance in bipolar disorder versus schizophrenia. Schizophr Res 2023; 252:1-9. [PMID: 36608492 PMCID: PMC9974828 DOI: 10.1016/j.schres.2022.12.034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Revised: 08/15/2022] [Accepted: 12/27/2022] [Indexed: 01/06/2023]
Abstract
INTRODUCTION Mood states have been reported to manifest a cross-sectional correlation with self-assessment accuracy across functional domains and psychiatric conditions. Ecological momentary assessment (EMA) provides a strategy to examine the momentary course and correlates of mood states. This study tested the association of moods assessed longitudinally with accuracy of immediate self-assessments of cognitive test performance in participants with schizophrenia and bipolar disorder. METHODS 240 well-diagnosed participants with schizophrenia and bipolar disorder completed a subset of tests from the MATRICS Consensus Cognitive Battery and an immediate self-assessment of cognitive performance. Differences between actual and self-reported performance were used to index the accuracy of self-assessment. Daily smartphone EMA, 3× per day for 30 days, sampled participants´ momentary moods (sad, happy, relaxed, anxious), aggregated into positive affect and negative affect (NA). RESULTS Bipolar participants had better cognitive performance, but both samples had equivalent mis-estimation. Repeated-measures analyses found that NA did not manifest significant variability over time either between or within participants in the two diagnostic groups. Within-group analyses found that higher average NA was associated with greater mis-estimation and poorer cognitive performance in participants with bipolar disorder, but not in those with schizophrenia. CONCLUSION Negative moods had a significant association with impairments in self-assessment of cognitive performance in participants with bipolar disorder. Our study did not confirm previous cross-sectional findings of more accurate self-assessment associated with greater NA in schizophrenia. These findings suggest that cross-sectional assessments, particularly self-reports, may lead to different results than aggregated data from longitudinal evaluations.
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Affiliation(s)
- Nina Dalkner
- Medical University Graz, Austria; University of Miami Miller School of Medicine, Miami, FL, USA
| | | | - Colin A Depp
- UCSD Health Sciences Center, La Jolla, CA, USA; San Diego VA Medical Center La Jolla, CA, USA
| | | | | | - Philip D Harvey
- University of Miami Miller School of Medicine, Miami, FL, USA; Bruce W. Carter VA Medical Center, Miami, FL, USA.
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Walsh RFL, Smith LT, Klugman J, Titone MK, Ng TH, Goel N, Alloy LB. An examination of bidirectional associations between physical activity and mood symptoms among individuals diagnosed and at risk for bipolar spectrum disorders. Behav Res Ther 2023; 161:104255. [PMID: 36682182 PMCID: PMC9909602 DOI: 10.1016/j.brat.2023.104255] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 09/19/2022] [Accepted: 01/15/2023] [Indexed: 01/19/2023]
Abstract
OBJECTIVES Activation, a construct including energy and activity, is a central feature of Bipolar Spectrum Disorders (BSDs). Prior research found motor activity is associated with affect, and this relationship may be stronger for individuals with BSDs. The aims of this study were to investigate bidirectional relationships between physical activity and mood and evaluate whether bipolar risk status moderated potential associations. METHODS Young adults at low-risk, high-risk, and diagnosed with BSD participated in a 20-day EMA study in which they wore an actiwatch to measure physical activity and sleep/wake cycles. They also reported depressive and hypo/manic symptoms three times daily. Multilevel linear models were estimated to examine how bipolar risk group moderated bidirectional relationships between physical activity and mood symptoms at within-day and between-day timescales. RESULTS Physical activity was significantly associated with subsequent mood symptoms at the within-day level. The relationship between physical activity and depressive symptoms was moderated by BSD risk group. An increase in physical activity resulted in a greater reduction of depressive symptoms for the BSD group compared to the low-risk and high-risk groups. CONCLUSIONS Interventions targeting activity like behavioral activation may improve residual inter-episode mood symptoms.
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Affiliation(s)
- Rachel F L Walsh
- Department of Psychology and Neuroscience, Temple University, USA
| | - Logan T Smith
- Department of Psychology and Neuroscience, Temple University, USA
| | - Joshua Klugman
- Department of Psychology and Neuroscience, Temple University, USA; Department of Sociology, Temple University, USA
| | - Madison K Titone
- VA San Diego Healthcare System, USA; University of California San Diego, USA
| | - Tommy H Ng
- Department of Psychiatry, Weill Cornell Medicine College, USA
| | - Namni Goel
- Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, USA
| | - Lauren B Alloy
- Department of Psychology and Neuroscience, Temple University, USA.
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Schick A, Rauschenberg C, Ader L, Daemen M, Wieland LM, Paetzold I, Postma MR, Schulte-Strathaus JCC, Reininghaus U. Novel digital methods for gathering intensive time series data in mental health research: scoping review of a rapidly evolving field. Psychol Med 2023; 53:55-65. [PMID: 36377538 PMCID: PMC9874995 DOI: 10.1017/s0033291722003336] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Revised: 09/13/2022] [Accepted: 10/05/2022] [Indexed: 11/16/2022]
Abstract
Recent technological advances enable the collection of intensive longitudinal data. This scoping review aimed to provide an overview of methods for collecting intensive time series data in mental health research as well as basic principles, current applications, target constructs, and statistical methods for this type of data.In January 2021, the database MEDLINE was searched. Original articles were identified that (1) used active or passive data collection methods to gather intensive longitudinal data in daily life, (2) had a minimum sample size of N ⩾ 100 participants, and (3) included individuals with subclinical or clinical mental health problems.In total, 3799 original articles were identified, of which 174 met inclusion criteria. The most widely used methods were diary techniques (e.g. Experience Sampling Methodology), various types of sensors (e.g. accelerometer), and app usage data. Target constructs included affect, various symptom domains, cognitive processes, sleep, dysfunctional behaviour, physical activity, and social media use. There was strong evidence on feasibility of, and high compliance with, active and passive data collection methods in diverse clinical settings and groups. Study designs, sampling schedules, and measures varied considerably across studies, limiting the generalisability of findings.Gathering intensive longitudinal data has significant potential to advance mental health research. However, more methodological research is required to establish and meet critical quality standards in this rapidly evolving field. Advanced approaches such as digital phenotyping, ecological momentary interventions, and machine-learning methods will be required to efficiently use intensive longitudinal data and deliver personalised digital interventions and services for improving public mental health.
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Affiliation(s)
- Anita Schick
- Department of Public Mental Health, Medical Faculty Mannheim, Central Institute of Mental Health, Heidelberg University, Heidelberg, Germany
| | - Christian Rauschenberg
- Department of Public Mental Health, Medical Faculty Mannheim, Central Institute of Mental Health, Heidelberg University, Heidelberg, Germany
| | - Leonie Ader
- Department of Public Mental Health, Medical Faculty Mannheim, Central Institute of Mental Health, Heidelberg University, Heidelberg, Germany
| | - Maud Daemen
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Lena M. Wieland
- Department of Public Mental Health, Medical Faculty Mannheim, Central Institute of Mental Health, Heidelberg University, Heidelberg, Germany
| | - Isabell Paetzold
- Department of Public Mental Health, Medical Faculty Mannheim, Central Institute of Mental Health, Heidelberg University, Heidelberg, Germany
| | - Mary Rose Postma
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Julia C. C. Schulte-Strathaus
- Department of Public Mental Health, Medical Faculty Mannheim, Central Institute of Mental Health, Heidelberg University, Heidelberg, Germany
| | - Ulrich Reininghaus
- Department of Public Mental Health, Medical Faculty Mannheim, Central Institute of Mental Health, Heidelberg University, Heidelberg, Germany
- Centre for Epidemiology and Public Health, Health Service and Population Research Department, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- ESRC Centre for Society and Mental Health, King's College London, London, UK
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Liu Y, Chen L, Zhou H, Guan H, Feng Y, Yangji B, Liu Q, Liu X, Xia J, Li J, Zhao X. Does awareness of diabetic status increase risk of depressive or anxious symptoms? Findings from the China Multi-Ethnic cohort (CMEC) study. J Affect Disord 2023; 320:218-229. [PMID: 36191641 DOI: 10.1016/j.jad.2022.09.135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Revised: 09/24/2022] [Accepted: 09/27/2022] [Indexed: 02/02/2023]
Abstract
INTRODUCTION People with diabetes mellitus (DM) have increased risk of depressive symptoms (DS) or anxious symptoms (AS). This study explores whether awareness of DM will contribute to prevalence of DS or AS. METHODS The baseline data including 81,717 adults from Southwest China was analyzed. DS and AS were assessed using PHQ-2 and GAD-2. Exposures were defined as 1) having self-reported physician diagnosis of diabetes (self-reported DM), 2) no prior diagnosis of diabetes but meeting diagnostic criteria (newly diagnosed DM), 3) having self-reported physician diagnosis or meeting criteria of non-diabetic diseases (non-diabetic patients), 4) healthy participants. Generalized linear mixed models were used to assess impact of presence and awareness of DM on DS or AS, adjusting for regional and individual related factors. RESULTS The prevalence of DS in self-reported DM, newly diagnosed DM, non-diabetic patient and healthy participants was 7.08 %, 4.30 %, 5.37 % and 3.17 %. The prevalence of AS was 7.80 %, 5.77 %, 6.37 % and 3.91 %. After adjusting for related factors, compared with healthy participants, self-reported DM and non-diabetic patients were associated with DS [AORDS, self-reported = 1.443(1.218,1.710), AORDS, nondiabetic patients = 1.265(1.143,1.400)], while the association between newly diagnosed DM and DS was not statistically significant. The associations between self-reported DM, newly diagnosed DM, non-diabetic patients and AS were all statistically significant. LIMITATIONS DS and AS were assessed through self-report and may suffer recall or information bias. CONCLUSIONS The association between awareness of diabetes and DS/AS suggests to pay attention to distinguish between self-reported and newly diagnosed DM and screening for DS and AS in diabetic population.
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Affiliation(s)
- Yuanyuan Liu
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Liling Chen
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, China
| | - Hanwen Zhou
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Han Guan
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Guizhou Medical University, Guiyang, Guizhou, China
| | - Yuemei Feng
- School of Public Health, Kunming Medical University, Kunming, Yunnan, China
| | - Baima Yangji
- School of Medicine, Tibet University, Lhasa, Tibet Autonomous Region, China
| | - Qiaolan Liu
- Department of Health Behavior and Social Medicine, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xiang Liu
- Department of Health Behavior and Social Medicine, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Jinjie Xia
- Chengdu Center for Disease Control and Prevention, Chengdu, Sichuan, China
| | - Jingzhong Li
- Tibet Center for Disease Control and Prevention, Lhasa, Tibet Autonomous Region, China
| | - Xing Zhao
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
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Walsh RFL, Smith LT, Titone MK, Ng TH, Goel N, Alloy LB. The relationship between physical activity states and depressive symptoms: Using ambulatory assessment to characterize day-to-day associations among individuals with and without bipolar spectrum disorder. Depress Anxiety 2022; 39:835-844. [PMID: 36254832 PMCID: PMC9729395 DOI: 10.1002/da.23290] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 08/19/2022] [Accepted: 10/02/2022] [Indexed: 01/27/2023] Open
Abstract
INTRODUCTION The role of activation in the pathogenesis of bipolar spectrum disorders (BSD) is of growing interest. Physical activity is known to improve mood, but it is unclear whether low activity levels contribute to inter-episode depressive symptoms observed in BSD. This study examined whether sedentary and vigorous activity, as well as the timing of the activity, were differentially associated with next-day depressive symptoms for individuals at low risk for BSD, high-risk for BSD, and diagnosed with BSD. METHODS Young adults (n = 111, ages 18-27) from three groups (low BSD risk, high BSD risk, and BSD diagnosis), participated in a 20-day ecological momentary assessment study. Physical activity was measured via wrist actigraphy counts. The percentage of time awake spent in sedentary, light, moderate, and vigorous activity states was calculated, as was the percentage of morning hours and evening hours in each activity state. Multilevel models examined whether the BSD risk group moderated associations between sedentary and vigorous activity and depressive symptoms, which were assessed three times daily. RESULTS There were no between-group differences in time spent in each activity state, nor were there main effects of sedentary or vigorous activity on depression. Increased time spent engaging in vigorous activity was associated with a greater reduction in subsequent depressive symptoms for the BSD group. An increase in the evening, but not morning, vigorous activity was significantly associated with a reduction in subsequent depressive symptoms for the BSD group after controlling for chronotype. CONCLUSIONS Interventions targeting physical activity may effectively help regulate inter-episode mood disturbances in BSD.
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Affiliation(s)
| | - Logan T. Smith
- Department of Psychology and Neuroscience, Temple University
| | | | - Tommy H. Ng
- Department of Psychiatry, Weill Cornell Medicine College
| | - Namni Goel
- Department of Psychiatry and Behavioral Sciences, Rush University Medical Center
| | - Lauren B. Alloy
- Department of Psychology and Neuroscience, Temple University
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Difrancesco S, Penninx BW, Merikangas KR, van Hemert AM, Riese H, Lamers F. Within-day bidirectional associations between physical activity and affect: A real-time ambulatory study in persons with and without depressive and anxiety disorders. Depress Anxiety 2022; 39:922-931. [PMID: 36345264 PMCID: PMC9729402 DOI: 10.1002/da.23298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/27/2022] [Revised: 10/25/2022] [Accepted: 10/30/2022] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND Ambulatory assessments offer opportunities to study physical activity level (PAL) and affect at the group and person-level. We examined bidirectional associations between PAL and affect in a 3-h timeframe and evaluated whether associations differ between people with and without current or remitted depression/anxiety. METHODS Two-week ecological momentary assessment (EMA) and actigraphy data of 359 participants with current (n = 93), remitted (n = 176), or no (n = 90) Composite International Diagnostic Interview depression/anxiety diagnoses were obtained from the Netherlands Study of Depression and Anxiety. Positive affect (PA) and negative affect (NA) were assessed by EMA 5 times per day. Average PAL between EMA assessments were calculated from actigraphy data. RESULTS At the group-level, higher PAL was associated with subsequent higher PA (b = 0.109, p < .001) and lower NA (b = -0.043, p < .001), while higher PA (b = 0.066, p < .001) and lower NA (b = -0.053, p < .001) were associated with subsequent higher PAL. The association between higher PAL and subsequent lower NA was stronger for current depression/anxiety patients than controls (p = .01). At the person-level, analyses revealed heterogeneity in bidirectional associations. CONCLUSIONS Higher PAL may improve affect, especially among depression/anxiety patients. As the relationships vary at the person-level, ambulatory assessments may help identify who would benefit from behavioral interventions.
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Affiliation(s)
- Sonia Difrancesco
- Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Psychiatry, Boelelaan 1117, Amsterdam, The Netherlands,Amsterdam Public Health, Mental Health program, Amsterdam, The Netherlands
| | - Brenda W.J.H. Penninx
- Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Psychiatry, Boelelaan 1117, Amsterdam, The Netherlands,Amsterdam Public Health, Mental Health program, Amsterdam, The Netherlands
| | - Kathleen R Merikangas
- Genetic Epidemiology Branch, Intramural Research Program, National Institute of Mental Health, Bethesda MD, USA
| | - Albert M. van Hemert
- Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands
| | - Harriëtte Riese
- University of Groningen, University Medical Center Groningen, Department of Psychiatry, Interdisciplinary Center for Psychopathology and Emotion regulation, Groningen, The Netherlands
| | - Femke Lamers
- Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Psychiatry, Boelelaan 1117, Amsterdam, The Netherlands,Amsterdam Public Health, Mental Health program, Amsterdam, The Netherlands
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Claudio A, Andrea F. Circadian neuromarkers of mood disorders. JOURNAL OF AFFECTIVE DISORDERS REPORTS 2022. [DOI: 10.1016/j.jadr.2022.100384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
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Svensson M, Erhardt S, Hållmarker U, James S, Deierborg T. A physically active lifestyle is associated with lower long-term incidence of bipolar disorder in a population-based, large-scale study. Int J Bipolar Disord 2022; 10:26. [DOI: 10.1186/s40345-022-00272-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Accepted: 09/27/2022] [Indexed: 11/05/2022] Open
Abstract
Abstract
Background
Physical activity has been proposed to be beneficial for the symptomatic control of bipolar disorder, but the duration of the effects, sex-specific mechanisms, and impact of exercise intensity are not known.
Method
With an observational study design, we followed skiers and age and sex-matched non-skiers from the general population to investigate if participation in a long-distance cross-country ski race (Vasaloppet) was associated with a lower risk of getting diagnosed with bipolar disorder. Using the Swedish population and patient registries, skiers in Vasaloppet and age and sex-matched non-skiers from the general population were analyzed for any diagnosis of bipolar disorder after participation in the race. Additionally, we used finishing time of the ski race as a proxy for intensity levels to investigate if exercise intensity impacts the risk of bipolar disorder among the physically active skiers.
Results
Previous participation in a long distance ski race (n = 197,685, median age 36 years, 38% women) was associated with a lower incidence of newly diagnosed bipolar compared to an age and sex-matched general population (n = 197,684) during the up to 21 years follow-up (adjusted hazard ratio, HR = 0.48). The finishing time of the race did not significantly impact the risk of bipolar disorder in men. Among women, high performance (measured as the finishing time to complete the race, a proxy for higher exercise dose) was associated with an increased risk of bipolar disorder compared to slower skiing women (HR = 2.07).
Conclusions
Our results confirm that a physically active lifestyle is associated with a lower risk of developing bipolar disorder. Yet, to elucidate the direction of causality in this relationship requires complementary study designs. And the influence of physical performance level on the risk of bipolar disorder warrants further examinations among women.
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McIntyre RS, Alda M, Baldessarini RJ, Bauer M, Berk M, Correll CU, Fagiolini A, Fountoulakis K, Frye MA, Grunze H, Kessing LV, Miklowitz DJ, Parker G, Post RM, Swann AC, Suppes T, Vieta E, Young A, Maj M. The clinical characterization of the adult patient with bipolar disorder aimed at personalization of management. World Psychiatry 2022; 21:364-387. [PMID: 36073706 PMCID: PMC9453915 DOI: 10.1002/wps.20997] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
Bipolar disorder is heterogeneous in phenomenology, illness trajectory, and response to treatment. Despite evidence for the efficacy of multimodal-ity interventions, the majority of persons affected by this disorder do not achieve and sustain full syndromal recovery. It is eagerly anticipated that combining datasets across various information sources (e.g., hierarchical "multi-omic" measures, electronic health records), analyzed using advanced computational methods (e.g., machine learning), will inform future diagnosis and treatment selection. In the interim, identifying clinically meaningful subgroups of persons with the disorder having differential response to specific treatments at point-of-care is an empirical priority. This paper endeavours to synthesize salient domains in the clinical characterization of the adult patient with bipolar disorder, with the overarching aim to improve health outcomes by informing patient management and treatment considerations. Extant data indicate that characterizing select domains in bipolar disorder provides actionable information and guides shared decision making. For example, it is robustly established that the presence of mixed features - especially during depressive episodes - and of physical and psychiatric comorbidities informs illness trajectory, response to treatment, and suicide risk. In addition, early environmental exposures (e.g., sexual and physical abuse, emotional neglect) are highly associated with more complicated illness presentations, inviting the need for developmentally-oriented and integrated treatment approaches. There have been significant advances in validating subtypes of bipolar disorder (e.g., bipolar I vs. II disorder), particularly in regard to pharmacological interventions. As with other severe mental disorders, social functioning, interpersonal/family relationships and internalized stigma are domains highly relevant to relapse risk, health outcomes, and quality of life. The elevated standardized mortality ratio for completed suicide and suicidal behaviour in bipolar disorder invites the need for characterization of this domain in all patients. The framework of this paper is to describe all the above salient domains, providing a synthesis of extant literature and recommendations for decision support tools and clinical metrics that can be implemented at point-of-care.
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Affiliation(s)
- Roger S. McIntyre
- Mood Disorders Psychopharmacology UnitUniversity Health NetworkTorontoONCanada,Department of PsychiatryUniversity of TorontoTorontoONCanada,Department of PharmacologyUniversity of TorontoTorontoONCanada
| | - Martin Alda
- Department of PsychiatryDalhousie UniversityHalifaxNSCanada,National Institute of Mental HealthKlecanyCzech Republic
| | - Ross J. Baldessarini
- Harvard Medical SchoolBostonMAUSA,International Consortium for Bipolar & Psychotic Disorders ResearchMcLean HospitalBelmontMAUSA,Mailman Research CenterMcLean HospitalBelmontMAUSA
| | - Michael Bauer
- University Hospital Carl Gustav CarusTechnische Universität DresdenDresdenGermany
| | - Michael Berk
- IMPACT Strategic Research Centre, School of MedicineDeakin UniversityGeelongVICAustralia,Orygen, National Centre of Excellence in Youth Mental HealthCentre for Youth Mental Health, University of MelbourneMelbourneVICAustralia
| | - Christoph U. Correll
- Department of PsychiatryZucker Hillside Hospital, Northwell HealthGlen OaksNYUSA,Department of Psychiatry and Molecular MedicineZucker School of Medicine at Hofstra/NorthwellHempsteadNYUSA,Department of Child and Adolescent PsychiatryCharité Universitätsmedizin BerlinBerlinGermany
| | | | - Kostas Fountoulakis
- 3rd Department of Psychiatry, Division of Neurosciences, School of MedicineAristotle University of ThessalonikiThessalonikiGreece
| | - Mark A. Frye
- Department of Psychiatry & PsychologyMayo ClinicRochesterMNUSA
| | - Heinz Grunze
- Allgemeinpsychiatrie OstKlinikum am WeissenhofWeinsbergGermany,Paracelsus Medical Private University NurembergNurembergGermany
| | - Lars V. Kessing
- Copenhagen Affective Disorder Research CenterPsychiatric Center CopenhagenCopenhagenDenmark,Faculty of Health and Medical SciencesUniversity of CopenhagenCopenhagenDenmark
| | - David J. Miklowitz
- Department of Psychiatry and Biobehavioral SciencesUniversity of California Los Angeles (UCLA) Semel InstituteLos AngelesCAUSA
| | - Gordon Parker
- School of PsychiatryUniversity of New South WalesSydneyNSWAustralia
| | - Robert M. Post
- School of Medicine & Health SciencesGeorge Washington UniversityWashingtonDCUSA,Bipolar Collaborative NetworkBethesdaMDUSA
| | - Alan C. Swann
- Department of PsychiatryBaylor College of MedicineHoustonTXUSA
| | - Trisha Suppes
- Department of Psychiatry and Behavioural SciencesStanford School of Medicine and VA Palo Alto Health Care SystemPalo AltoCAUSA
| | - Eduard Vieta
- Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Hospital ClinicUniversity of Barcelona, IDIBAPS, CIBERSAMBarcelonaCataloniaSpain
| | - Allan Young
- Department of Psychological Medicine, Institute of Psychiatry, Psychology, and NeuroscienceKing's College LondonLondonUK,South London and Maudsley NHS Foundation TrustBethlem Royal HospitalBeckenhamUK
| | - Mario Maj
- Department of PsychiatryUniversity of Campania “L. Vanvitelli”NaplesItaly
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Durdurak BB, Altaweel N, Upthegrove R, Marwaha S. Understanding the development of bipolar disorder and borderline personality disorder in young people: a meta-review of systematic reviews. Psychol Med 2022; 52:1-14. [PMID: 36177878 PMCID: PMC9816307 DOI: 10.1017/s0033291722003002] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Revised: 08/31/2022] [Accepted: 09/06/2022] [Indexed: 01/21/2023]
Abstract
BACKGROUND There is ongoing debate on the nosological position of bipolar disorder (BD) and borderline personality disorder (BPD). Identifying the unique and shared risks, developmental pathways, and symptoms in emerging BD and BPD could help the field refine aetiological hypotheses and improve the prediction of the onset of these disorders. This study aimed to: (a) systematically synthesise the available evidence from systematic reviews (SRs) and meta-analyses (MAs) concerning environmental, psychosocial, biological, and clinical factors leading to the emergence of BD and BPD; (b) identify the main differences and common features between the two disorders to characterise their complex interplay and, (c) highlight remaining evidence gaps. METHODS Data sources were; PubMed, PsychINFO, Embase, Cochrane, CINAHL, Medline, ISI Web of Science. Overlap of included SRs/MAs was assessed using the corrected covered area process. The methodological quality of each included SR and MA was assessed using the AMSTAR. RESULTS 22 SRs and MAs involving 249 prospective studies met eligibility criteria. Results demonstrated that family history of psychopathology, affective instability, attention deficit hyperactivity disorder, anxiety disorders, depression, sleep disturbances, substance abuse, psychotic symptoms, suicidality, childhood adversity and temperament were common predisposing factors across both disorders. There are also distinct factors specific to emerging BD or BPD. CONCLUSIONS Prospective studies are required to increase our understanding of the development of BD and BPD onset and their complex interplay by concurrently examining multiple measures in BD and BPD at-risk populations.
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Affiliation(s)
- Buse Beril Durdurak
- Institute for Mental Health, School of Psychology, University of Birmingham, Birmingham, UK
| | - Nada Altaweel
- Institute for Mental Health, School of Psychology, University of Birmingham, Birmingham, UK
| | - Rachel Upthegrove
- Institute for Mental Health, School of Psychology, University of Birmingham, Birmingham, UK
- Early Intervention Service, Birmingham Women's and Children's NHS Foundation Trust, Birmingham, UK
| | - Steven Marwaha
- Institute for Mental Health, School of Psychology, University of Birmingham, Birmingham, UK
- Specialist Mood Disorders Clinic, Birmingham and Solihull Mental Health NHS Foundation Trust, Birmingham, UK
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Meyer N, Harvey AG, Lockley SW, Dijk DJ. Circadian rhythms and disorders of the timing of sleep. Lancet 2022; 400:1061-1078. [PMID: 36115370 DOI: 10.1016/s0140-6736(22)00877-7] [Citation(s) in RCA: 72] [Impact Index Per Article: 36.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Revised: 03/20/2022] [Accepted: 05/05/2022] [Indexed: 02/06/2023]
Abstract
The daily alternation between sleep and wakefulness is one of the most dominant features of our lives and is a manifestation of the intrinsic 24 h rhythmicity underlying almost every aspect of our physiology. Circadian rhythms are generated by networks of molecular oscillators in the brain and peripheral tissues that interact with environmental and behavioural cycles to promote the occurrence of sleep during the environmental night. This alignment is often disturbed, however, by contemporary changes to our living environments, work or social schedules, patterns of light exposure, and biological factors, with consequences not only for sleep timing but also for our physical and mental health. Characterised by undesirable or irregular timing of sleep and wakefulness, in this Series paper we critically examine the existing categories of circadian rhythm sleep-wake disorders and the role of the circadian system in their development. We emphasise how not all disruption to daily rhythms is driven solely by an underlying circadian disturbance, and take a broader, dimensional approach to explore how circadian rhythms and sleep homoeostasis interact with behavioural and environmental factors. Very few high-quality epidemiological and intervention studies exist, and wider recognition and treatment of sleep timing disorders are currently hindered by a scarcity of accessible and objective tools for quantifying sleep and circadian physiology and environmental variables. We therefore assess emerging wearable technology, transcriptomics, and mathematical modelling approaches that promise to accelerate the integration of our knowledge in sleep and circadian science into improved human health.
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Affiliation(s)
- Nicholas Meyer
- Insomnia and Behavioural Sleep Medicine Clinic, University College London Hospitals NHS Foundation Trust, London, UK; Department of Psychosis Studies, Institute of Psychology, Psychiatry, and Neuroscience, King's College London, London, UK
| | - Allison G Harvey
- Department of Psychology, University of California, Berkeley, CA, USA
| | - Steven W Lockley
- Division of Sleep and Circadian Disorders, Department of Medicine and Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA; Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA; Surrey Sleep Research Centre, Department of Clinical and Experimental Medicine, University of Surrey, Guildford, UK
| | - Derk-Jan Dijk
- Surrey Sleep Research Centre, Department of Clinical and Experimental Medicine, University of Surrey, Guildford, UK; UK Dementia Research Institute, Care Research and Technology Centre, Imperial College London and the University of Surrey, Guildford, UK.
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Carpenter JS, Zmicerevska N, Crouse JJ, Nichles A, Garland A, Song YJC, Wilson C, Rohleder C, McHugh C, Leweke FM, Koethe D, Scott EM, Hickie IB. Effects of adjunctive brexpiprazole on sleep-wake and circadian parameters in youth with depressive disorders: study protocol for a clinical trial. BMJ Open 2022; 12:e056298. [PMID: 36691133 PMCID: PMC9454051 DOI: 10.1136/bmjopen-2021-056298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Accepted: 08/09/2022] [Indexed: 01/26/2023] Open
Abstract
INTRODUCTION Sleep-wake and circadian disturbance is a key feature of mood disorders with a potential causal role and particular relevance to young people. Brexpiprazole is a second-generation antipsychotic medication with demonstrated efficacy as an adjunct to antidepressant treatment for major depressive disorder (MDD) in adults, with preliminary evidence suggesting greater effectiveness in subgroups of depressed patients with sleep disturbances. This clinical trial aims to evaluate the relationships between changes in sleep-wake and circadian parameters and changes in depressive symptoms following adjunctive brexpiprazole treatment in young adults with MDD and sleep-wake disturbance. METHODS AND ANALYSIS This study is designed as a 16 week (8 weeks active treatment, 8 weeks follow-up) mechanistic, open-label, single-arm, phase IV clinical trial and aims to recruit 50 young people aged 18-30 with MDD and sleep-wake cycle disturbance through an early intervention youth mental health clinic in Sydney, Australia. At baseline, participants will undergo multidimensional outcome assessment and subsequently receive 8 weeks of open-label treatment with brexpiprazole as adjunctive to their stable psychotropic medication. Following 4 weeks of treatment, clinical and self-report measures will be repeated. Ambulatory sleep-wake monitoring will be conducted continuously for the duration of treatment. After 8 weeks of treatment, all multidimensional outcome assessments will be repeated. Follow-up visits will be conducted 4 and 8 weeks after trial completion (including sleep-wake, clinical and self-report assessments). Circadian rhythm biomarkers including salivary melatonin, cortisol and core body temperature will be collected during an in-lab assessment. Additionally, metabolic, inflammatory and genetic risk markers will be collected at baseline and after 8 weeks of treatment. ETHICS AND DISSEMINATION This trial protocol has been approved by the Human Research Ethics Committee of the Sydney Local Health District (X19-0417 and 2019/ETH12986, Protocol Version 1-3, dated 25 February 2021). The results of this study, in deidentified form, will be disseminated through publication in peer-reviewed journals, scholarly book chapters, presentation at conferences and publication in conference proceedings. TRIAL REGISTRATION NUMBER ACTRN12619001456145.
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Affiliation(s)
- Joanne S Carpenter
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - Natalia Zmicerevska
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - Jacob J Crouse
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - Alissa Nichles
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - Alexandra Garland
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - Yun Ju Christine Song
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - Chloe Wilson
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - Cathrin Rohleder
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - Catherine McHugh
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - F Markus Leweke
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - Dagmar Koethe
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - Elizabeth M Scott
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
- The University of Notre Dame Australia School of Medicine Sydney Campus, Darlinghurst, New South Wales, Australia
| | - Ian B Hickie
- Brain and Mind Centre, The University of Sydney, Camperdown, New South Wales, Australia
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Rohr KE, McCarthy MJ. The impact of lithium on circadian rhythms and implications for bipolar disorder pharmacotherapy. Neurosci Lett 2022; 786:136772. [PMID: 35798199 DOI: 10.1016/j.neulet.2022.136772] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Accepted: 07/01/2022] [Indexed: 01/21/2023]
Abstract
Bipolar disorder (BD) is characterized by disrupted circadian rhythms affecting sleep, arousal, and mood. Lithium is among the most effective mood stabilizer treatments for BD, and in addition to improving mood symptoms, stabilizes sleep and activity rhythms in treatment responsive patients. Across a variety of experimental models, lithium has effects on circadian rhythms. However, uncertainty exists as to whether these actions directly pertain to lithium's therapeutic effects. Here, we consider evidence from mechanistic studies in animals and cells and clinical trials in BD patients that identify associations between circadian rhythms and the therapeutic effects of lithium. Most evidence indicates that lithium has effects on cellular circadian rhythms and increases morningness behaviors in BD patients, changes that may contribute to the therapeutic effects of lithium. However, much of this evidence is limited by cross-sectional analyses and/or imprecise proxy markers of clinical outcomes and circadian rhythms in BD patients, while mechanistic studies rely on inference from animals or small numbers of patients . Further study may clarify the essential mechanisms underlying lithium responsive BD, better characterize the longitudinal changes in circadian rhythms in BD patients, and inform the development of therapeutic interventions targeting circadian rhythms.
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Affiliation(s)
- Kayla E Rohr
- Department of Psychiatry and Center For Circadian Biology, University of California San Diego, La Jolla, CA, USA
| | - Michael J McCarthy
- Department of Psychiatry and Center For Circadian Biology, University of California San Diego, La Jolla, CA, USA; Mental Health Service, VA San Diego Healthcare System, La Jolla, CA, USA.
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41
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Bourke M, Patten RK, Klamert L, Klepac B, Dash S, Pascoe MC. The acute affective response to physical activity in people with depression: A meta-analysis. J Affect Disord 2022; 311:353-363. [PMID: 35605707 DOI: 10.1016/j.jad.2022.05.089] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 05/09/2022] [Accepted: 05/15/2022] [Indexed: 11/12/2022]
Abstract
BACKGROUND Little is known about the acute affective response to physical activity in people with depression, which may have implications for acute symptom management and may also be a mechanism that explains the antidepressant effects of physical activity. This study aimed to quantitatively synthesize existing research on the acute affective response to physical activity in people with depression. METHODS Five online databases were searched to July 2021 to identify studies that examined pre-post changes in affective states following a bout of moderate-to-vigorous physical activity in people with depression. The affective response to physical activity was synthesized using a random-effects meta-analysis with a robust variance estimator. RESULTS A total of 18 studies were included in the meta-analysis. Results showed that people with depression experienced a favourable affective response following an acute bout of physical activity (SMD = 0.585, 95% confidence interval = [0.456, 0.714], 95% prediction interval = [-0.079, 1.249]). Moderator analysis indicated this effect was consistent across different types of affective states, exercise conditions, and participant characteristics. Additionally, results were robust to changes in the study protocol and publication bias. LIMITATIONS Only within-person pre-post changes in affective responses were examined. No comparisons were made with control conditions. CONCLUSION Acute bouts of physical activity can significantly improve affective states in people with depression. Future research should examine the effect of physical activity on affective states in non-experimental settings and examine whether the affective response to physical activity is a predictor of the long-term antidepressant effects of physical activity interventions.
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Affiliation(s)
- Matthew Bourke
- Institute for Health and Sport, Victoria University, Melbourne, Australia.
| | - Rhiannon K Patten
- Institute for Health and Sport, Victoria University, Melbourne, Australia
| | - Lisa Klamert
- Institute for Health and Sport, Victoria University, Melbourne, Australia
| | - Bojana Klepac
- Mitchell Institute for Education and Health Policy, Victoria University, Melbourne, Australia
| | - Sarah Dash
- Institute for Health and Sport, Victoria University, Melbourne, Australia; Deakin University, IMPACT - the Institute for Mental and Physical Health and Clinical Translation, Food & Mood Centre, School of Medicine, Barwon Health, Geelong, Australia
| | - Michaela C Pascoe
- Institute for Health and Sport, Victoria University, Melbourne, Australia
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Ma Y, Zhang B, Meng Y, Cao Y, Mao Y, Qiu C. Perceived stress and depressive symptoms among Chinese college students: A moderated mediation model of biorhythm and ego resilience. Front Public Health 2022; 10:951717. [PMID: 35991064 PMCID: PMC9386344 DOI: 10.3389/fpubh.2022.951717] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 07/04/2022] [Indexed: 11/30/2022] Open
Abstract
Objective To explore whether biological rhythm disturbance mediates the association between perceived stress and depressive symptoms and to investigate whether ego resilience moderates the mediation model. Methods A cross-sectional study was carried out using an online self-report questionnaire distributed to college students from September 2021 to October 2021. Patient Health Questionnaire-9 (PHQ-9), Perceived Stress Severity (PSS-10), the Biological Rhythms Assessment in Neuropsychiatry (BRIAN), and Ego Resilience (ER-96) were used for investigation. SPSS 23 was used for data analyses. The significance of mediation was determined by the PROCESS macro using a bootstrap approach. Results Among the participants, 9.2% (N = 1,282) exhibited significant symptoms of depression. Perceived stress was positively associated with depressive symptoms, and biorhythm partially mediated this relationship. The direct and indirect effects were both moderated by ego resilience. Perceived stress had a greater impact on depressive symptoms and biorhythm for college students with lower ego resilience, and the impact of biorhythm on depressive symptoms was also stronger for those with lower ego resilience. Perceived stress had an impact on depressive symptoms directly and indirectly via the mediation of biorhythm. Conclusion Schools and educators should guide college students to identify stress correctly and provide effective suggestions to deal with it. Meanwhile, maintaining a stable biorhythm can protect college students from developing depressive symptoms. Students with low resilience should be given more attention and assistance.
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Affiliation(s)
- Yao Ma
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Baiyang Zhang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yajing Meng
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Yuan Cao
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
- Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu, China
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Yineng Mao
- School of Public Health, North Sichuan Medical College, Nanchong, China
| | - Changjian Qiu
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
- *Correspondence: Changjian Qiu
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Federoff M, McCarthy MJ, Anand A, Berrettini WH, Bertram H, Bhattacharjee A, Calkin CV, Conroy C, Coryell WH, D'Arcangelo N, DeModena A, Fisher C, Feeder S, Frazier N, Frye MA, Gao K, Garnham J, Gershon ES, Alliey-Rodriguez N, Glazer K, Goes F, Karberg T, Harrington G, Jakobsen P, Kamali M, Kelly M, Leckband SG, Lohoff F, Maihofer AX, McInnis MG, Mondimore F, Morken G, Nurnberger JI, Oedegaard KJ, Ritchey M, Ryan K, Schinagle M, Schoeyen H, Schwebel C, Shaw M, Shilling PD, Slaney C, Stautland A, Tarwater B, Calabrese JR, Alda M, Nievergelt CM, Zandi PP, Kelsoe JR. Correction of depression-associated circadian rhythm abnormalities is associated with lithium response in bipolar disorder. Bipolar Disord 2022; 24:521-529. [PMID: 34825444 DOI: 10.1111/bdi.13162] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
BACKGROUND Bipolar disorder (BD) is characterized by episodes of depression and mania and disrupted circadian rhythms. Lithium is an effective therapy for BD, but only 30%-40% of patients are fully responsive. Preclinical models show that lithium alters circadian rhythms. However, it is unknown if the circadian rhythm effects of lithium are essential to its therapeutic properties. METHODS In secondary analyses of a multi-center, prospective, trial of lithium for BD, we examined the relationship between circadian rhythms and therapeutic response to lithium. Using standardized instruments, we measured morningness, diurnal changes in mood, sleep, and energy (circadian rhythm disturbances) in a cross-sectional study of 386 BD subjects with varying lithium exposure histories. Next, we tracked symptoms of depression and mania prospectively over 12 weeks in a subset of 88 BD patients initiating treatment with lithium. Total, circadian, and affective mood symptoms were scored separately and analyzed. RESULTS Subjects with no prior lithium exposure had the most circadian disruption, while patients stable on lithium monotherapy had the least. Patients who were stable on lithium with another drug or unstable on lithium showed intermediate levels of disruption. Treatment with lithium for 12 weeks yielded significant reductions in total and affective depression symptoms. Lithium responders (Li-Rs) showed improvement in circadian symptoms of depression, but non-responders did not. There was no difference between Li-Rs and nonresponders in affective, circadian, or total symptoms of mania. CONCLUSIONS Exposure to lithium is associated with reduced circadian disruption. Lithium response at 12 weeks was selectively associated with the reduction of circadian depressive symptoms. We conclude that stabilization of circadian rhythms may be an important feature of lithium's therapeutic effects. CLINICAL TRIALS REGISTRY NCT0127253.
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Affiliation(s)
- Monica Federoff
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
| | - Michael J McCarthy
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,Department of Psychiatry, VA San Diego Healthcare System, La Jolla, California, USA
| | - Amit Anand
- Department of Psychiatry, Case Western Reserve University, Cleveland, Ohio, USA
| | - Wade H Berrettini
- University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | | | - Abesh Bhattacharjee
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,Department of Psychiatry, VA San Diego Healthcare System, La Jolla, California, USA
| | | | - Carla Conroy
- Department of Psychiatry, Case Western Reserve University, Cleveland, Ohio, USA
| | | | - Nicole D'Arcangelo
- Department of Psychiatry, Case Western Reserve University, Cleveland, Ohio, USA
| | - Anna DeModena
- Department of Psychiatry, VA San Diego Healthcare System, La Jolla, California, USA
| | - Carrie Fisher
- Departments of Psychiatry and Medical and Molecular Genetics, Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | | | | | | | - Keming Gao
- Department of Psychiatry, Case Western Reserve University, Cleveland, Ohio, USA
| | | | | | | | - Kara Glazer
- Department of Psychiatry and Behavioral Sciences, The Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Fernando Goes
- Department of Psychiatry and Behavioral Sciences, The Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Toyomi Karberg
- Department of Psychiatry, Case Western Reserve University, Cleveland, Ohio, USA
| | | | - Petter Jakobsen
- NORMENT, Division of Psychiatry, Haukeland University Hospital, Bergen, Norway.,Department of Clinical Medicine, University of Bergen, Norway
| | | | - Marisa Kelly
- University of Michigan, Ann Arbor, Michigan, USA
| | - Susan G Leckband
- Department of Psychiatry, VA San Diego Healthcare System, La Jolla, California, USA
| | - Falk Lohoff
- University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Adam X Maihofer
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
| | | | - Francis Mondimore
- Department of Psychiatry and Behavioral Sciences, The Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Gunnar Morken
- Division of Psychiatry, St. Olav University Hospital of Trondheim and Department of Neuroscience, Faculty of Medicine, Norwegian University of Science and Technology, Trondheim, Norway
| | - John I Nurnberger
- Departments of Psychiatry and Medical and Molecular Genetics, Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Ketil J Oedegaard
- NORMENT, Division of Psychiatry, Haukeland University Hospital, Bergen, Norway.,Department of Clinical Medicine, University of Bergen, Norway
| | - Megan Ritchey
- Department of Psychiatry and Behavioral Sciences, The Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Kelly Ryan
- University of Michigan, Ann Arbor, Michigan, USA
| | - Martha Schinagle
- Department of Psychiatry, Case Western Reserve University, Cleveland, Ohio, USA
| | - Helle Schoeyen
- Department of Clinical Medicine, University of Bergen, Norway.,Clinic of Adult Psychiatry, Stavanger University Hospital, Stavanger, Norway
| | - Candice Schwebel
- University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Martha Shaw
- University of Chicago, Chicago, Illinois, USA
| | - Paul D Shilling
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
| | | | | | | | - Joseph R Calabrese
- Department of Psychiatry, Case Western Reserve University, Cleveland, Ohio, USA
| | | | - Caroline M Nievergelt
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
| | - Peter P Zandi
- Department of Psychiatry and Behavioral Sciences, The Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - John R Kelsoe
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
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Shrestha R, Maviglia F, Altice FL, DiDomizio E, Khati A, Mistler C, Azwa I, Kamarulzaman A, Halim MAA, Wickersham JA. Mobile Health Technology Use and the Acceptability of an mHealth Platform for HIV Prevention Among Men Who Have Sex With Men in Malaysia: Cross-sectional Respondent-Driven Sampling Survey. J Med Internet Res 2022; 24:e36917. [PMID: 35877172 PMCID: PMC9361153 DOI: 10.2196/36917] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2022] [Revised: 04/14/2022] [Accepted: 05/08/2022] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND The growth in mobile technology access, utilization, and services holds great promise in facilitating HIV prevention efforts through mobile health (mHealth) interventions in Malaysia. Despite these promising trends, there is a dearth of evidence on the use of mHealth platforms that addresses HIV prevention among Malaysian men who have sex with men. OBJECTIVE The goal of this study was to gain insight into (1) access and utilization of communication technology (eg, landline phone, internet, mobile phone), (2) acceptability of mHealth-based interventions for HIV prevention services, and (3) preferences regarding the format and frequency of mHealth interventions among Malaysian men who have sex with men. METHODS We conducted a cross-sectional survey with Malaysian men who have sex with men between July 2018 and March 2020. Participants were recruited using respondent-driven sampling in the Greater Kuala Lumpur region of Malaysia. We collected information on demographic characteristics, HIV risk-related behaviors, access to and the frequency of use of communication technology, and acceptability of using mHealth for HIV prevention using a self-administered questionnaire with a 5-point scale (1, never; 2, rarely; 3, sometimes; 4, often; 5, all the time). RESULTS A total of 376 men participated in the survey. Almost all respondents owned or had access to a smartphone with internet access (368/376, 97.9%) and accessed the internet daily (373/376, 99.2%), mainly on a smartphone (334/376, 88.8%). Participants on average used smartphones primarily for social networking (mean 4.5, SD 0.8), followed by sending or receiving emails (mean 4.0, SD 1.0), and searching for health-related information (mean 3.5, SD 0.9). There was high acceptance of the use of mHealth for HIV prevention (mean 4.1, SD 1.5), including for receiving HIV prevention information (345/376, 91.8%), receiving medication reminders (336/376, 89.4%), screening and monitoring sexual activity (306/376, 81.4%) or illicit drug use (281/376, 74.7%), and monitoring drug cravings (280/376, 74.5%). Participants overwhelmingly preferred a smartphone app over other modalities (eg, text, phone call, email) for engaging in mHealth HIV prevention tools. Preference for app notifications ranged from 186/336 (53.9%), for receiving HIV prevention information, to 212/336 (69.3%), for screening and monitoring sexual activity. Acceptance of mHealth was higher for those who were university graduates (P=.003), living in a relationship with a partner (P=.04), engaged in sexualized drug use (P=.01), and engaged in receptive anal sex (P=.006). CONCLUSIONS Findings from this study provide support for developing and deploying mHealth strategies for HIV prevention using a smartphone app in men who have sex with men-a key population with suboptimal engagement in HIV prevention and treatment.
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Affiliation(s)
- Roman Shrestha
- Department of Allied Health Sciences, University of Connecticut, Storrs, CT, United States
| | - Francesca Maviglia
- Section of Infectious Diseases, Yale University, New Haven, CT, United States
| | - Frederick L Altice
- Section of Infectious Diseases, Yale University, New Haven, CT, United States
| | - Elizabeth DiDomizio
- Section of Infectious Diseases, Yale University, New Haven, CT, United States
| | - Antoine Khati
- Department of Allied Health Sciences, University of Connecticut, Storrs, CT, United States
| | - Colleen Mistler
- Department of Allied Health Sciences, University of Connecticut, Storrs, CT, United States
| | - Iskandar Azwa
- Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
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Quick CR, Conway KP, Swendsen J, Stapp EK, Cui L, Merikangas KR. Comorbidity and Coaggregation of Major Depressive Disorder and Bipolar Disorder and Cannabis Use Disorder in a Controlled Family Study. JAMA Psychiatry 2022; 79:727-735. [PMID: 35648395 PMCID: PMC9161121 DOI: 10.1001/jamapsychiatry.2022.1338] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
IMPORTANCE Cannabis use disorder (CUD) is increasing in the US. Clarification of the potential mechanisms underlying the comorbidity between mood disorders and CUD may help prevent CUD. OBJECTIVE To examine co-occurrence and familial aggregation of CUD and mood disorder subtypes. DESIGN, SETTING, AND PARTICIPANTS In this cross-sectional, community-based study in the Washington, DC, metropolitan area, semistructured diagnostic interviews and family history reports assessed lifetime DSM-IV disorders in probands and relatives. Familial aggregation and coaggregation of CUD with mood disorders were estimated via mixed-effects models, adjusting for age, sex, recruitment source, and comorbid mood, anxiety, and other substance use disorders. A total of 586 adult probands (186 with bipolar disorder; 55 with CUD) and 698 first-degree relatives (91 with bipolar disorder; 68 with CUD) were recruited from a community screening of the greater Washington, DC, metropolitan area from May 2004 to August 2020. Inclusion criteria were ability to speak English, and availability and consent to contact at least 2 living first-degree relatives. MAIN OUTCOMES AND MEASURES Lifetime CUD in first-degree relatives. RESULTS Of 586 probands, 395 (67.4%) were female; among 698 relatives, 437 (62.6%) were female. The mean (SD) age was 47.5 (15.2) years for probands and 49.6 (18.0) years for relatives. In the proband group, 82 participants (14.0%) self-identified as African American or Black, 467 (79.7%) as White, and 37 (6.3%) as American Indian or Alaska Native, Asian, more than one race, or another race or ethnicity or declined to respond. In the relative group, 53 participants (7.6%) self-identified as African American or Black, 594 (85.1%) as White, and 51 (7.3%) as American Indian or Alaska Native, Asian, more than one race, or another race or ethnicity or declined to respond. These groups were combined to protect privacy owing to small numbers. CUD in probands (55 [9.4%]) was associated with an increase in CUD in relatives (adjusted odds ratio [aOR], 2.64; 95% CI, 1.20-5.79; P = .02). Bipolar disorder II (BP-II) in probands (72 [12.3%]) was also associated with increased risk of CUD in relatives (aOR, 2.57; 95% CI, 1.06-6.23; P = .04). However, bipolar disorder I (114 [19.5%]) and major depressive disorder (192 [32.8%]) in probands were not significantly associated with CUD in relatives. Among relatives, CUD was associated with BP-II (aOR, 4.50; 95% CI, 1.72-11.77; P = .002), major depressive disorder (aOR, 3.64; 95% CI, 1.78-7.45; P < .001), and mean (SD) age (42.7 [12.8] years with CUD vs 50.3 [18.3] years without CUD; aOR, 0.98; 95% CI, 0.96-1.00; P = .02). Familial coaggregation of BP-II with CUD was attenuated by the inclusion of comorbid anxiety disorders. Further, rates of CUD were highest in relatives with both a familial and individual history of BP-II (no familial or individual history of BP-II: 41 [7.2%]; familial history but no individual history of BP-II: 13 [19.1%]; individual history but no familial history of BP-II: 10 [22.2%]; familial and individual history of BP-II: 4 [28.6%]; Fisher exact test, P < .001). The onset of mood disorder subtypes preceded CUD in probands and relatives in most cases. CONCLUSIONS AND RELEVANCE The findings confirmed a familial aggregation of CUD. The increase in risk of CUD among relatives of probands with BP-II suggests that CUD may share a common underlying diathesis with BP-II. Taken together with the temporal precedence of depression and mania with respect to CUD onset, these findings highlight a potential role for BP-II intervention as CUD prevention.
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Affiliation(s)
- Courtney R. Quick
- Genetic Epidemiology Branch, Intramural Research Program, National Institute of Mental Health, Bethesda, Maryland
| | - Kevin P. Conway
- Genetic Epidemiology Branch, Intramural Research Program, National Institute of Mental Health, Bethesda, Maryland
| | - Joel Swendsen
- Aquitaine Institute for Cognitive and Integrative Neuroscience, University of Bordeaux, Bordeaux, France
| | - Emma K. Stapp
- Genetic Epidemiology Branch, Intramural Research Program, National Institute of Mental Health, Bethesda, Maryland
| | - Lihong Cui
- Genetic Epidemiology Branch, Intramural Research Program, National Institute of Mental Health, Bethesda, Maryland
| | - Kathleen R. Merikangas
- Genetic Epidemiology Branch, Intramural Research Program, National Institute of Mental Health, Bethesda, Maryland
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Mazzotti DR, Haendel MA, McMurry JA, Smith CJ, Buysse DJ, Roenneberg T, Penzel T, Purcell S, Redline S, Zhang Y, Merikangas KR, Menetski JP, Mullington J, Boudreau E. Sleep and circadian informatics data harmonization: a workshop report from the Sleep Research Society and Sleep Research Network. Sleep 2022; 45:zsac002. [PMID: 35030631 PMCID: PMC9189941 DOI: 10.1093/sleep/zsac002] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Revised: 12/21/2021] [Indexed: 01/16/2023] Open
Abstract
The increasing availability and complexity of sleep and circadian data are equally exciting and challenging. The field is in constant technological development, generating better high-resolution physiological and molecular data than ever before. Yet, the promise of large-scale studies leveraging millions of patients is limited by suboptimal approaches for data sharing and interoperability. As a result, integration of valuable clinical and basic resources is problematic, preventing knowledge discovery and rapid translation of findings into clinical care. To understand the current data landscape in the sleep and circadian domains, the Sleep Research Society (SRS) and the Sleep Research Network (now a task force of the SRS) organized a workshop on informatics and data harmonization, presented at the World Sleep Congress 2019, in Vancouver, Canada. Experts in translational informatics gathered with sleep research experts to discuss opportunities and challenges in defining strategies for data harmonization. The goal of this workshop was to fuel discussion and foster innovative approaches for data integration and development of informatics infrastructure supporting multi-site collaboration. Key recommendations included collecting and storing findable, accessible, interoperable, and reusable data; identifying existing international cohorts and resources supporting research in sleep and circadian biology; and defining the most relevant sleep data elements and associated metadata that could be supported by early integration initiatives. This report introduces foundational concepts with the goal of facilitating engagement between the sleep/circadian and informatics communities and is a call to action for the implementation and adoption of data harmonization strategies in this domain.
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Affiliation(s)
- Diego R Mazzotti
- Division of Medical Informatics, Department of Internal Medicine, University of Kansas Medical Center, Kansas City, KS, USA
- Division of Pulmonary Critical Care and Sleep Medicine, Department of Internal Medicine, University of Kansas Medical Center, Kansas City, KS, USA
| | - Melissa A Haendel
- Center for Health AI, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Julie A McMurry
- Center for Health AI, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Connor J Smith
- Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA
| | - Daniel J Buysse
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA,USA
| | - Till Roenneberg
- Institute and Polyclinic for Occupational-, Social- and Environmental Medicine, LMU Munich, Germany
| | - Thomas Penzel
- Interdisciplinary Center of Sleep Medicine, Charité University Hospital, Berlin, Germany
| | - Shaun Purcell
- Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Susan Redline
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Ying Zhang
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Kathleen R Merikangas
- Genetic Epidemiology Research Branch, Intramural Research Program, National Institute of Mental Health, Bethesda, MD, USA
| | | | - Janet Mullington
- Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Eilis Boudreau
- Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA
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Temporal relationships of ecological momentary mood and actigraphy-based sleep measures in bipolar disorder. J Psychiatr Res 2022; 150:257-263. [PMID: 35405410 PMCID: PMC9107496 DOI: 10.1016/j.jpsychires.2022.03.055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/12/2021] [Revised: 03/16/2022] [Accepted: 03/31/2022] [Indexed: 02/01/2023]
Abstract
Sleep disturbances are a key feature of bipolar disorder (BD), and poor sleep has been linked to mood symptoms. Recent use of ecological momentary assessment (EMA) has allowed for nuanced exploration of the sleep-mood link; though, the scale and directionality of this relationship is still unclear. Using EMA, actigraphy, and self-reported sleep measures, this study examines the concurrent and predictive relationships between sleep and mood. Participants with BD (n = 56) wore actigraphy devices for up to 14 days and completed validated scales and daily EMA surveys about mood and sleep quality. Linear mixed models were used to examine overall and time-lagged relationships between sleep and mood variables. EMA mood ratings were correlated with validated rating scales for depression, mania, anxiety, and impulsivity. Poor self-reported sleep quality was associated with worse overall ratings of sadness and anger. Worse self-reported sleep quality was associated with greater sadness the following day. Higher daytime impulsivity was associated with worse sleep quality the following night. Exploratory analyses found relationships between worse and more variable mood (sadness, anger, and impulsivity) with worse and more variable sleep that evening (efficiency, WASO, and sleep onset time). The sample size was modest, fairly homogenous, and included mainly euthymic persons with BD. EMA-based assessments of mood and sleep are correlated with validated scale scores and provide novel insight into intra-individual variability. Further work on the complex two-way interactions between sleep and mood is needed to better understand how to improve outcomes in BD.
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Miller ML, Raugh IM, Strauss GP, Harvey PD. Remote digital phenotyping in serious mental illness: Focus on negative symptoms, mood symptoms, and self-awareness. Biomark Neuropsychiatry 2022. [DOI: 10.1016/j.bionps.2022.100047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/19/2022] Open
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A network analysis of rest-activity rhythms in young people with emerging bipolar disorders. J Affect Disord 2022; 305:220-226. [PMID: 35288205 DOI: 10.1016/j.jad.2022.03.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Revised: 02/17/2022] [Accepted: 03/07/2022] [Indexed: 11/21/2022]
Abstract
AIMS Actigraphy studies of individuals with bipolar disorders (BD) suggest that illness progression may be associated with a range of progressive disruptions in 24-hour rest-activity rhythms (RAR). However, those longitudinal studies were undertaken in older adults with extended histories or illness and treatment rather than young people with emerging BD. To our knowledge, this is the first study to use network modelling to examine the statistical associations between clinical phenotypes of BD and different subsets of RAR markers. METHODS This study of adolescents and young adults (mean age 22 years; 69% female) uses network modelling to examine which self-rated or actigraphic markers of RAR are more strongly associated with full threshold BD (referred to as Stage 2; N = 15) compared with BD-at risk syndromes (subthreshold presentations referred to as Stage 1; N = 25). RESULTS Network analysis demonstrated that some RAR are associated with both stage of BD and a family history of BD (such as longer sleep duration and higher levels of daytime impairment). Markers of circadian rhythmicity indicated that regulation of this system is weaker in Stage 2 compared with Stage 1 of BD. LIMITATIONS The small subgroup samples may have undermined the ability to detect some associations between phenotypes and RAR. CONCLUSIONS Network modelling may offer a useful strategy for visualizing and analysing patterns of association between RAR and clinical phenotypes defined by stage of illness, familial loading or symptom profile. This could prove useful in understanding the underlying pathophysiology of sleep-wake cycle and circadian rhythm disturbances in BD.
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50
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Porras-Segovia A, Díaz-Oliván I, Barrigón ML, Moreno M, Artés-Rodríguez A, Pérez-Rodríguez MM, Baca-García E. Real-world feasibility and acceptability of real-time suicide risk monitoring via smartphones: A 6-month follow-up cohort. J Psychiatr Res 2022; 149:145-154. [PMID: 35276631 DOI: 10.1016/j.jpsychires.2022.02.026] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 01/31/2022] [Accepted: 02/28/2022] [Indexed: 12/21/2022]
Abstract
Active and passive Ecological Momentary Assessment of suicide risk is crucial for suicide prevention. We aimed to assess the feasibility and acceptability of active and passive smartphone-based EMA in real-world conditions in patients at high risk for suicide. We followed 393 patients at high risk for suicide for six months using two mobile health applications: the MEmind (active) and the eB2 (passive). Retention with active EMA was 79.3% after 1 month and 22.6% after 6 months. Retention with passive EMA was 87.8% after 1 month and 46.6% after 6 months. Satisfaction with the MEmind app, uninstalling the eB2 app and diagnosis of eating disorders were independently associated with stopping active EMA. Satisfaction with the eB2 app and uninstalling the MEmind app were independently associated with stopping passive EMA. Smartphone-based active and passive EMA are feasible and may increase accessibility to mental healthcare.
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Affiliation(s)
- Alejandro Porras-Segovia
- Instituto de Investigación Sanitaria Fundación Jiménez Díaz, Madrid, Spain; Departamento de Psiquiatría, Hospital Universitario Rey Juan Carlos, Móstoles, Spain
| | | | - Maria Luisa Barrigón
- Instituto de Investigación Sanitaria Fundación Jiménez Díaz, Madrid, Spain; Universidad Autónoma de Madrid, Madrid, Spain; Departamento de Psiquiatría, Hospital Universitario Fundación Jiménez Díaz, Madrid, Spain
| | | | - Antonio Artés-Rodríguez
- Department of Signal Theory, Universidad Carlos III de Madrid, Leganés, Spain; Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain
| | | | - Enrique Baca-García
- Instituto de Investigación Sanitaria Fundación Jiménez Díaz, Madrid, Spain; Departamento de Psiquiatría, Hospital Universitario Rey Juan Carlos, Móstoles, Spain; Universidad Autónoma de Madrid, Madrid, Spain; Departamento de Psiquiatría, Hospital Universitario Fundación Jiménez Díaz, Madrid, Spain; CIBERSAM, Spain; Departamento de Psiquiatría, Hospital Universitario Infanta Elena, Valdemoro, Madrid, Spain; Departamento de Psiquiatría, Hospital Universitario Central de Villalba, Madrid, Spain; Universidad Católica del Maule, Talca, Chile; Department of Psychiatry, Centre Hospitalier Universitaire de Nîmes, France.
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